JP2000057134A - Documentation device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reduce the load on a user and also to make effectively performable input support. SOLUTION: The same character string check processing part 36 checks whether or not a character string part matching with another character string exists, to each character string of an input predictive candidate, about the input predictive candidate which is obtained by retrieving an input predictive dictionary 86 based on an inputted read character string and is stored in an input predictive candidate storing part 88. And, an input predictive candidate integrating processing part 38 integrates an input predictive candidate which is discriminated as having a character string part that coincides with another character string to a simplified character string. An input predictive candidate display processing part 34 shows a character string integrated to the simplified character string together with the character string of an input predictive candidate that is not integrated as an input predictive candidate to an inputted read character string.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a document creation device such as a Japanese word processor, and more particularly to a character input by kana-kanji conversion as well as an input reading character string and other characters related to the reading character string. The present invention relates to a document creation device that converts a sequence into columns (input prediction processing, seamless input processing) and inputs the converted data.

[0002]

2. Description of the Related Art Generally, in a document creation device such as a Japanese word processor, in order to improve the efficiency of character input,
There is a method in which a long character string is registered as a short character string and treated as a Kana-Kanji conversion user dictionary, so that the user can input a long character string simply by inputting a short character string. .

However, in this method, since a character string must be registered in advance, it is actually difficult to employ the above-described method for every character string.

[0004] On the other hand, in a recent document creation device,
A method of improving input efficiency by performing input prediction processing has been used. In the input prediction process, when the user reads the first several characters of a reading character string, the input prediction dictionary is searched using these several characters as a search key, and a character string (word) starting with these several characters is extracted. Display and selectable as an input string,
A character string subsequent to the first few characters can be easily input, and the user's trouble of inputting can be saved.

For example, Japanese Patent Application No. 7-56315 (Japanese Patent Application Laid-Open No. 8-255156) discloses a document creating apparatus in which the input efficiency is improved by performing the above-described input prediction processing.

As a method for improving the efficiency of character input, an input support process (hereinafter, referred to as a seamless input process) for reducing the operation burden of switching input modes.
Is used. In this seamless input process, when entering characters of multiple character types, such as hiragana, katakana, alphabets, and numbers, included in the created document,
A character of a desired character type can be input without successively changing the input mode by operating the shift control key.

For example, Japanese Patent Application No. Hei 6-176734 (Japanese Patent Application Laid-Open No. Hei 8-44725) does not require an operation for switching the input character type (operation on a shift control key).
A document creation device capable of creating a document in which a character type different from a kana character is mixed has been disclosed.

In this document creation device, the input character type is changed to English characters, and the input English words are registered in the user dictionary by reading the kana characters (the sequence of kana characters of the same key). When this word is input by reading a kana character, the English word can be read from the user dictionary and output based on the reading. This eliminates the need to switch the input character type when the same word is input for the second and subsequent times.

[0009]

As described above, in a conventional document creation apparatus, a method using an input prediction process or a seamless input process is used to improve the efficiency of character input for document creation. Was. In addition, a dictionary is constructed by using information of a user who is in the process of creating a document, thereby improving the efficiency of the input support function.

However, if the dictionary is searched based on the input character string and the corresponding candidates are displayed, the number of candidates to be presented may become too large, or the same candidates may be continuously input. Even if it is performed, the display may continue, and the user may be burdened when selecting a desired one from the candidates.

In a configuration in which a user registers information in a dictionary based on information input to create a document, even if the user edits the information previously input, the contents of the edit are stored in the dictionary. Can not be reflected in That is, there is a demand for more effective use of input support that is suitable for a user by making more effective use of input information and registering it in a dictionary.

Further, since the input prediction processing and the seamless input processing are handled as independent functions, the efficiency is not totally improved.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and has as its object to provide a document creation apparatus capable of reducing the load on a user and effectively providing input support. .

[0014]

SUMMARY OF THE INVENTION First, the present invention relates to an input prediction candidate obtained by searching an input prediction dictionary based on an input reading character string. Then, it is checked whether or not there is a character string portion that matches another character string. Then, the input prediction candidates for which it is determined that there is a character string portion that matches another character string are integrated into a simplified character string and displayed together with the character strings of the input prediction candidates that are not integrated.

Secondly, the present invention relates to a method of converting an input reading character string and a conversion result character string obtained by the kana-kanji conversion means for the reading character string into a reading corresponding to each character of the conversion result character string. When the stored conversion result character string is edited, the input read character string and the conversion result character string are updated in accordance with the content of the editing. The read character string updated in accordance with this editing and the conversion result character string are registered in association with the read character string of the input prediction dictionary and the input prediction candidate, and used for the input prediction processing for the input read character string. I do.

Third, the present invention automatically registers a conversion result character string obtained by performing a kana-kanji conversion on an input reading character string as a character string of an input prediction candidate in an input prediction dictionary in a predetermined character string unit. deep. Then, the kana-kanji conversion is internally performed on the input reading character string, the input prediction dictionary is searched based on the character string obtained as a result, and input prediction candidates are obtained and displayed. As a result, if the character string of the input prediction candidate selected is a character string automatically registered earlier, the character string stored in the input prediction dictionary is subjected to the internal kana-kanji conversion target. Character strings are stored in association with each other.

According to a fourth aspect of the present invention, a kana-kanji conversion dictionary is searched based on an input reading character string, a character string of a headword as a conversion candidate is obtained, and based on the input reading character string. Then, a seamless input dictionary is searched, and a heading, which is a character string of another character type different from the kana character corresponding to the input reading character string, is obtained and added to the conversion candidates obtained by the kana-kanji conversion.

According to a fifth aspect of the present invention, a search is made to determine whether or not an input character string contains an arbitrary character or a special character representing a character string. Search the input prediction dictionary based on the searched special characters and the input reading character string, and obtain an input prediction candidate that is a character string that is likely to be input following the current input character string. .

According to a sixth aspect of the present invention, a seamless input dictionary is searched based on an input reading character string, and the character string is a character string of another character type different from the kana character corresponding to the input reading character string. Searches for an input prediction dictionary based on a character string obtained by searching for a headline and a seamless dictionary, and input prediction candidates that are likely to be input following the current input character string , And the character string found by searching the seamless dictionary and the character string found by searching the input prediction dictionary are displayed as conversion candidates for the input reading character string.

According to a seventh aspect of the present invention, the input prediction dictionary is searched based on the input read character string, and the input prediction candidate which is a character string which is likely to be input following the input character string up to the present time. Is obtained and stored, and displayed. If the input prediction candidate obtained based on the subsequently-input reading character string is the same as the previously stored input prediction candidate, the The number of times is counted, and when the counted number reaches a predetermined value, the input prediction candidate stored is erased and the display is erased.

[0021]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing the system configuration of the document creation device according to the present embodiment.
The document creation device according to the present embodiment is, for example, a CD-RO
It is realized by a computer which reads a program recorded on a recording medium such as an M, DVD, or magnetic disk, and whose operation is controlled by the program.

As shown in FIG. 1, a document creation device according to the present embodiment includes a CPU 10, a memory 12, an input device 1
4, a display device 16 and a storage device 18.

The CPU 10 controls the entire apparatus, and realizes various functions by executing based on programs and data stored in the memory 12. In the present embodiment, the kana-kanji conversion process, the input prediction process, the seamless input process, and the like are executed by executing the document creation control program 12b stored in the memory 12.

The memory 12 is a read-only or readable / writable memory device by the CPU 10 or the like, and stores programs and data. Various programs such as a control program 12a and a document creation control program 12b are stored in a program area provided in the memory 12. It is assumed that the document creation control program 12b includes various programs for realizing kana-kanji conversion processing, input prediction processing, seamless input processing, and the like.

The memory 12 has a document information section 12c.
In addition, an information storage unit 12d in which various information is stored according to the execution status of the program is provided. The document information section 12c includes data such as a document created by the document creation process. Further, the information storage unit 12d includes data used when performing a kana-kanji conversion process, an input prediction process, a seamless input process, and the like, and stores data read from the storage device 18 as necessary. .

The input device 14 is a pointing device such as a keyboard or a mouse or a pen for inputting data to be processed or a command for the device. When creating a document, a keyboard is mainly used. Each key of this keyboard is a character key for inputting character data, a conversion key for instructing execution of kana-kanji conversion for the input character string, a direction indication for various selections Various functions are assigned, such as up / down / left / right cursor keys for inputting a key, and selection keys for instructing confirmation of various selections.

The display device 16 displays input data and output results and includes a liquid crystal display, a CRT, and the like, and a controller.

The storage device 18 is a device for storing various data including the information storage section 18a, programs 18b, and the like. The storage device 18 is a hard disk, a CD-R
Programs recorded on recording media such as OM, DVD, floppy disk (document creation control program 12b, etc.)
Can be read and executed by the document creation device. The information storage unit 18a stores various dictionaries used in kana-kanji conversion processing, input prediction processing, seamless input processing, and the like, processing data, and the like.

Next, each of the embodiments (first to seventh embodiments) will be described.

First, a first embodiment will be described. In the first embodiment, when a plurality of input prediction candidates are obtained by an input prediction process performed based on an input reading character string, the input prediction candidates having a common notation with others are integrated. Displaying in a list facilitates selection by the user.

FIG. 2 shows a control program 12a and a document creation control program 1 in the system configuration shown in FIG.
FIG. 2 is a block diagram illustrating a functional configuration of the document creation device according to the first embodiment that is realized by executing 2b.

As shown in FIG. 2, the document creation device according to the first embodiment has the functions of an input control processing unit 22, an output control processing unit 24, a document creation control unit 26, and an information storage unit 28. ing.

The input control processing unit 22 controls the control program 1
2a is executed by inputting data, instructions, and the like from the input device 14 (for example, a keyboard). When the document creation processing is being executed, the input character data is stored in the input character string storage unit 80 of the information storage unit 28.
To be stored. Further, an instruction corresponding to a function assigned to a key of the input device 14 (keyboard) is input.

The output control processing unit 24 controls the control program 1
2a, and controls the display device 16 to display a document created by the kana-kanji conversion process and various information associated with the input prediction process and the seamless input process. The information output destination is not limited to the display device 16, but may be a printing device, a communication device, a storage device, or the like.

The document creation control unit 26 controls the control program 1
2a, which is realized by executing the document creation control program 12b, and executes a process of creating a document by performing kana-kanji conversion processing, input prediction processing, and seamless input processing on input character data. The document creation control unit 26 has the following functions in order to improve the user's input efficiency for document creation.

As shown in FIG. 2, the document creation control unit 26 includes a kana-kanji conversion processing unit 30, an input prediction dictionary search processing unit 32, an input prediction candidate display processing unit 34, an input prediction candidate selection processing unit 35, and the same character string. Check processing unit 36, display confirmation position control processing unit 37, and input prediction candidate integration processing unit 38
Each function is included.

The information storage unit 28 stores an input character string storage unit 80 and a kana-kanji conversion dictionary 8 in order to store data used by each function provided in the document creation control unit 26.
2, a conversion result storage unit 84, an input prediction dictionary 86, and an input prediction candidate storage unit 88 are provided.

The kana-kanji conversion processing unit 30 performs kana-kanji conversion on the input character string stored in the input character string storage unit 80 based on the dictionary data stored in the kana-kanji conversion dictionary 82, Is stored in the conversion result storage unit 84. The kana-kanji conversion processing unit 30 converts an input character string using a character string of a heading obtained by an input prediction candidate obtained by the input prediction processing (input prediction dictionary search processing unit 32).

The input prediction dictionary search processing unit 32 searches the input prediction dictionary 86 based on the input character strings stored in the input character string storage unit 80, and is input following the input character strings up to now. An input prediction candidate that is a possible input character string is obtained and stored in the input prediction candidate storage unit 88.

The input prediction candidate display processing section 34 causes the display device 16 to display a plurality of input prediction candidates stored in the input prediction candidate storage section 88 through the output control processing section 24.

The input prediction candidate selection processing unit 35 converts the conversion candidates displayed by the input prediction candidate display processing unit 34 into
Select a character string to be a conversion result according to an external instruction.

The same character string check processing unit 36 matches each character string of the input prediction candidate searched by the input prediction dictionary search processing unit 32 and stored in the input prediction candidate storage unit 88 with another character string. Check if there is a character string part.

The display confirmation position control processing unit 37 checks the reference position (display confirmation position (display confirmation position) for the input prediction candidate when the same character string check processing unit 36 checks whether there is a character portion that matches another character string. loc)).

The input prediction candidate integration processing unit 38 converts the character string of the input prediction candidate determined by the same character string check processing unit 36 as having a character string portion that matches another character string,
The data is integrated into a simplified character string and stored in the input prediction candidate storage unit 88. Note that the relationship between the simplified character string and the integrated plurality of input prediction candidate character strings is managed, and a plurality of integrated input prediction candidates based on the simplified character string can be obtained. .

The input character string storage section 80 stores the input device 14,
An input character string to be processed, which is input through the input control processing unit 22, is stored.

The conversion result storage unit 84 stores the results (conversion candidates) of the kana-kanji conversion of the character string stored in the input character string storage unit 80 by the kana-kanji conversion processing unit 30.

The kana-kanji conversion dictionary 82 is referred to when performing the kana-kanji conversion by the kana-kanji conversion processing section 30. The kana-kanji conversion dictionary 82 registers a reading character string and a character string of a headword as a conversion result in association with each other. I have.

The input prediction dictionary 86 is referred to by the input prediction dictionary search processing unit 32 when executing the input prediction processing, and includes a read character string, a character string of a headword as an input prediction candidate, and other information. Are registered in association with each other. Details of the information stored in the input prediction dictionary 86 will be described later (FIG. 4).

The input prediction candidate storage unit 88 stores the search result of the input prediction dictionary 86 by the input prediction dictionary search processing unit 32, and is used as an output buffer for displaying a list of input prediction candidates. In the first embodiment, the input prediction candidate integration processing unit 38 includes a simplified character string obtained by integrating a plurality of input prediction candidate character strings.

Next, the operation of the document creation apparatus according to the first embodiment will be described with reference to the flowchart shown in FIG.

First, when a character string is input to the input character string storage unit 80 via the input control processing unit 22, the input prediction dictionary search processing unit 32 converts the input character string stored in the input character string storage unit 80 into an input character string. Then, a search is performed for the reading of the input prediction dictionary 86, and if there is a corresponding input prediction candidate, all the candidates are stored in the input prediction candidate storage unit 88 (step A1).

It is assumed that information as shown in FIG. 4 is stored in the input prediction dictionary 86. That is, a reading to be searched by the input reading character string,
The character strings of the corresponding headings are stored in association with each other. The input prediction dictionary search processing unit 32 searches for the reading of the input prediction dictionary 86 based on the input reading character string, and obtains the input prediction dictionary 86 having the same reading from the head as an input prediction candidate together with the heading.

When an input prediction candidate corresponding to the character string is found in the input character string (step A2), the display confirmation position control processing unit 37 sets the display confirmation position (loc) to 1 and checks the same character string. The character position to be checked by the processing unit 36 is set as the first character (step A
3).

The same character string check processing unit 36 determines whether there is another input prediction candidate whose character position indicated by the display confirmation position (loc) set by the display confirmation position control processing unit 37 has the same notation. A check is made for each of the input prediction candidates stored in the input prediction candidate storage unit 88 (step A4).

When there is an input prediction candidate having the same notation at the character position indicated by the display confirmation position (loc), the same character string check processing unit 36 outputs a different notation besides the input prediction candidate having the same notation. It is determined whether or not there is a candidate (step A5). That is, it is determined whether or not there is a description common to all input prediction candidates. If there is a notation common to all input prediction candidates, it is meaningless to integrate all input prediction candidates based on this notation,
The display confirmation position control processing unit 37 outputs the display confirmation position (lo
One is added to the value of c) (step A11), and the same processing is repeatedly executed based on the next display confirmation position (steps A4 to A4).

On the other hand, when there is a candidate whose notation is different in the character position indicated by the display confirmation position (loc), the input prediction candidate integration processing unit 38 uses the same notation as the character position indicated by the display confirmation position (loc). The character strings of the input prediction candidates that have been changed are combined into one (step A6). Further, the input prediction candidate integration processing unit 38 outputs the current display confirmation position (lo
c) A character string portion (n characters) up to a different notation after the next character after c) is written, and a character string that is written using a specific symbol, for example, a dot sequence "..." is generated and input. It is stored in the prediction candidate storage unit 88 (step A7). The specific symbol is not limited to the dot sequence “...”, And may be any special character indicating that it is integrated. Further, the display confirmation position control processing unit 37 adds the number of characters (n) of the character string part having the same notation in the integrated input prediction candidate to (loc) and adds the display confirmation position (lo).
c) (Step A7).

The input prediction candidate display processing section 34 displays a list display of the input prediction candidates retrieved by the input prediction dictionary retrieval processing section 32, which are integrated by the input prediction candidate integration processing section 38 and other candidates. Device 16
(Step A8). The user is allowed to select a conversion result for the input character string from the list of input prediction candidates (step A9).

When an input prediction candidate is selected from the list display, the input prediction candidate selection processing unit 35 determines whether the input prediction candidate is a candidate integrated by the input prediction candidate integration processing unit 38 (step A10). If the input prediction candidate is not an integrated input prediction candidate, the selected input prediction candidate is displayed as a conversion result instead of the input reading character string.

On the other hand, if the input prediction candidate is an integrated input prediction candidate, the display confirmation position control
The value of oc) is incremented by 1 (step A11), and the above-described processing is executed in the integrated plurality of input prediction candidates (step A12). That is, if there are a plurality of input prediction candidates having the same character string portion in the description, they are integrated and displayed. When the display confirmation position (loc) is updated and there is no character at the corresponding character position, the process is terminated.

Next, a specific embodiment of the first embodiment will be described.

For example, when the reading character string “KABU” is input, as a result of searching the input prediction dictionary 86 shown in FIG.
"Corporation""Established""Founded"
Sub-organizations, General Meeting of Shareholders, Buying and Selling Shares, Buying Shares
“Trade” is obtained as an input prediction candidate. In this case, input prediction candidates other than “subordinate organization” can be combined into one based on the notation of the first character “stock”. Therefore,
As shown in FIG. 5 (a), a list of input prediction candidates of "stock ..." and "substructure" is displayed.

Here, when the input prediction candidate of "stock ..." is selected by the user, the other input prediction candidates that have been combined into one, based on the notation of the first character "stock",
A plurality of input prediction candidates are further combined into one by a common notation portion after “stock”.

In this case, as shown in FIG.
Since there are a plurality of input prediction candidates having the common name of "stock company", those characters are combined into one by using the input prediction candidates of "stock company ...". Other input prediction candidates having no common notation are listed. In addition, since there is a common character string in the notation “stock”, these input prediction candidates are also combined into one.

Here, when the input prediction candidate of "shares ..." is selected, the input prediction candidates "buy stocks" and "trade and buy stocks" combined by the "stocks ..." Since they cannot be put together, they are displayed individually as shown in FIG.

Here, when the input prediction candidate of "purchase stock" is selected, "purchase stock" is displayed in place of the input reading character string "kabu" as shown in FIG. 5D. You.

When "corporation ..." is selected in the list of input prediction candidates shown in FIG. 6B, among the plurality of input prediction candidates grouped by the input prediction candidates, "stock" The input prediction candidates of “company”, that is, the input prediction candidates that are the same as the notation common to the others are displayed in the list, and the other input prediction candidates are displayed in an integrated form.

Here, when the user selects an input prediction candidate of “corporate” from the list display, instead of the input reading character string “kabu”, as shown in FIG. Is displayed.

That is, by displaying a list of input prediction candidates in a format as shown in FIG. 6C, the same character string as the notation common to other input prediction candidates (for example, Since the input prediction candidates are grouped (for example, “stock company...”), They can be easily selected from the list display.

Note that the display screen shown in FIG.
It may be displayed as shown in (e). That is, by increasing the length of the character string of the common notation, if there is one input prediction candidate that cannot be combined, one input prediction candidate that has been combined with that notation and one input prediction candidate that has not been combined Display a list of candidates. By displaying in this manner, the character string of “stock company” as the input prediction candidate can be selected with a small number of operations.

As described above, with respect to a plurality of input prediction candidates obtained based on the input reading character string, a character string having a common notation with other input prediction candidates is integrated and displayed. Selection by the user can be facilitated.

Next, a second embodiment will be described.

In the second embodiment, a character string created by Kana-Kanji conversion of an input character string is automatically registered in the input prediction dictionary 86 so that the contents of editing on the result of Kana-Kanji conversion can be reflected. I do.

FIG. 7 shows a control program 12a and a document creation control program 1 in the system configuration shown in FIG.
FIG. 9 is a block diagram illustrating a functional configuration of a document creation device according to a second embodiment, which is realized by executing 2b.
The same components as those in FIG. 2 described in the first embodiment are denoted by the same reference numerals, and detailed description is omitted.

The character positional relationship storage processing unit 40 determines the heading stored in the kana-kanji conversion dictionary 82 of the conversion result and the heading corresponding to the input reading character string and the result of the kana-kanji conversion for this character string. The relationship with the input reading is stored in the character position relationship table 90.

The character positional relationship update processing unit 41 updates the reading and heading information in accordance with the editing of the kana-kanji conversion result stored in the character positional relationship table 90.

The character editing processing section 42 includes the input control processing section 2
In response to the instruction input through the Kana-Kanji 2, the Kana-Kanji conversion result is edited, and the contents are notified to the character position relationship update processing unit 41.

The input prediction candidate registration processing unit 43 stores the input reading character string stored in the character positional relationship table 90 and the result of the Kana-Kanji conversion for this character string in the input prediction dictionary 86 as a reading and a heading, respectively. Register automatically.

The character positional relationship table 90 stores the input reading character string and the result of the Kana-Kanji conversion for this character string as a set of readings corresponding to each character of the heading, that is, each character as an editing unit. It is a table for.

It is assumed that the reading and heading information are stored in the kana-kanji conversion dictionary 82 in association with each other as shown in FIG. That is, for each character string used as a heading, its reading is registered for each character. For example,
For the heading "Creation", a reading "Saku" corresponding to "Saku" and a reading "Sei" corresponding to "Naru" are registered.

Next, the operation of the second embodiment will be described with reference to FIG.
This will be described with reference to the flowchart shown in FIG.

First, when an input character string is stored in the input character string storage unit 80 via the input control processing unit 22, the kana-kanji conversion processing unit 30 converts the input reading character string into a kana-kanji conversion dictionary 82 And converts the kana-kanji conversion, and stores the conversion result in the conversion result storage unit 84 (step B1).

On the other hand, the character position relation storage processing section 40 stores a character position relation table 90 for matching the read character string for each character of the heading notation as the conversion result with respect to the kana-kanji conversion result by the kana-kanji conversion processing section 30. Create and store (step B2).

For example, as shown in FIG. 11 (a), when a hiragana character string “going through the syllabary” is input and kana-kanji conversion is executed,
As shown in FIG. 1 (b), it is assumed that a conversion result (candidate) of “creating a document while predicting” is obtained.

In this case, the character position relation storage processing unit 40
As shown in FIG. 10A, for each character of the heading stored in the Kana-Kanji conversion dictionary 82 of the Kana-Kanji conversion result, the reading is registered as a set in the character position relation table 90. Each character of the heading stored in the character position relation table 90 is a unit when editing is performed, and a position is designated by a cursor when editing is performed.

For example, with respect to the result of the kana-kanji conversion as shown in FIG. 11B, the cursor is moved to the position of "sentence" as shown in FIG. 11C (step B3),
As shown in FIG. 11D, when the reading character string “Bunsho” for correction is input and the kana-kanji conversion is executed, the character editing processing unit 42 returns to the original as shown in FIG. Replace the character string of "document" of the sentence with "sentence".

When the character editing unit 42 edits a character string converted into Kana-Kanji characters, the character position relation update processing unit 41 sends the edited conversion result stored in the character position relation table 90, that is, The character "sentence""book" at the position designated by the cursor is updated to "sentence""chapter", and the reading corresponding to each heading is updated to "bun""sho".

After the character string obtained by the Kana-Kanji conversion is edited, the cursor is moved to the position shown in FIG.
As shown in (f), when the input prediction candidate registration processing unit 43 is moved to a position other than the character string resulting from the kana-kanji conversion (step B4), the contents stored in the character position relation table 90 are subjected to input prediction. It is registered in the dictionary 86 as an input predicted new word.

That is, as shown in FIG. 12, the input reading dictionary is prepared by associating the input reading “producing a sentence while escaping” with the heading “producing a text while predicting”. Register at 86.

As described above, the input prediction candidate can be automatically acquired while the document is being created, and can be registered in the input prediction dictionary 86. Therefore, the document can be created using the newly registered prediction candidate. Thus, it is possible to reduce the load on the user when creating a document. In particular, since the input reading character string and the result of the Kana-Kanji conversion for this character string are not stored in the input prediction dictionary 86 in units, the result of editing the arbitrarily specified character can be reflected. It is possible to register an input prediction candidate that suits the user's preference.

In the example shown in FIG. 12, it has been described that the edited reading registered in the character positional relationship table 90 and the character string of the heading are stored in the input prediction dictionary 86 in association with each other. In the same manner as the conversion dictionary, by registering the reading for each character of the heading in association with each other, when an input prediction candidate registered as a new word in the input prediction dictionary 86 by the input prediction process is input as a conversion result When the character string is edited, the result of the editing may be further reflected and automatically registered in the input prediction dictionary 86.

If all the input prediction candidates registered in the input prediction dictionary 86 are registered in the same manner in which each character of the heading and each reading are associated with each other, the above-described processing is performed for all the input prediction candidates. In this way, the content of the editing can be reflected in the input prediction dictionary 86 and registered.

Next, a third embodiment will be described.

The third embodiment relates to automatic acquisition of candidates, and enables automatic input prediction candidates to be obtained from character strings created by kana-kanji conversion (determined as conversion results and having no reading information). .

FIG. 13 shows a control program 12a and a document creation control program 1 in the system configuration shown in FIG.
It is a block diagram showing the functional composition of the document creation device in a 3rd embodiment realized by performing 2b.
The same components as those in FIG. 2 described in the first embodiment are denoted by the same reference numerals, and detailed description is omitted.

The internal kana-kanji conversion control processing unit 45 performs the kana-kanji conversion processing unit 30 internally when the reading character string is input to the input character string storage unit 80 without instructing the execution of the kana-kanji conversion. The kana-kanji conversion is executed with reference to the dictionary 82.

The second input prediction dictionary search processing unit 46 searches the input prediction dictionary 86 based on the result of the kana-kanji conversion performed by the control of the internal kana-kanji conversion control processing unit 45, and obtains a corresponding input prediction candidate. .

If the input prediction candidate searched by the second input prediction dictionary search processing unit 46 is an input prediction candidate for which no reading information is registered, the reading provision processing unit 47 performs an internal kana-kanji conversion control processing unit. The character string of the reading that has been converted at the time of the Kana-Kanji conversion performed under the control of 45 is registered in association with a predicted word (described later) stored in the input prediction dictionary 86.

The predicted phrase automatic registration processing unit 48 obtains the kana-kanji conversion obtained by the kana-kanji conversion processing unit 30.
A predetermined character string unit, for example, a character string delimited by punctuation is extracted from the kana-kanji conversion result (having no reading information) stored in the conversion result storage unit 84 and registered in the input prediction dictionary 86 as a predicted word. .

Next, a third embodiment will be described with reference to a flowchart shown in FIG.

First, when a read character string is stored in the input character string storage section 80, the kana-kanji conversion processing section 30 executes kana-kanji conversion with reference to the kana-kanji conversion dictionary 82, and stores the result in the conversion result storage section 84. To be stored. Here, it is assumed that the conversion result stored in the conversion result storage unit 84 is a character string determined by a user's instruction.

When the determined character string is stored in the conversion result storage unit 84, the predicted phrase automatic registration processing unit 48 fetches the determined character string (step C1) and converts the character string into a predetermined character string unit. For example, a character string obtained by dividing a part having punctuation marks is registered as a predicted word in the heading of the input prediction dictionary 86 (step C2).

For example, when a character string as shown in FIG. 15A is stored in the conversion result storage unit 84, the predicted phrase automatic registration processing unit 48 uses the punctuation mark as shown in FIG. The three delimited character strings are stored in the input prediction dictionary 86 as predicted words.

On the other hand, if a kana-reading character string is input for creating a normal document (step C3), and the kana-kanji conversion is executed (step C4), the kana-kanji conversion processing section 30 outputs the input. The kana-kanji conversion is performed on the read character string (step C5), and the conversion result is stored in the conversion result storage unit 84. In this case, a character string of the conversion result is displayed instead of the input reading character string.

On the other hand, when the kana-kanji conversion is not instructed, the input prediction dictionary search processing section 32 searches the input prediction dictionary 86 based on the input character string stored in the input character string storage section 80, and It is determined whether there is a prediction candidate corresponding to the read character string (step C6).
The input prediction candidate is stored in the input prediction candidate storage unit 88. In this case, the input prediction candidate display processing unit 34 causes the display device 16 to display the input prediction candidates stored in the input prediction candidate storage unit 88 via the output control processing unit 24 (Step C9).

If the input prediction dictionary search processing unit 32 searches the input prediction dictionary 86 and finds no corresponding input prediction candidate (step C6), the internal kana-kanji conversion control processing unit 45 sets the input character string The kana-kanji conversion processing unit 30 internally performs kana-kanji conversion on the input read character string stored in the storage unit 80 (step C7). When performing the internal kana-kanji conversion, the kana-kanji conversion processing unit 30 stores the conversion result in the conversion result storage unit 84 and does not display the conversion result.

For example, as shown in FIG. 15 (b), when a reading character string "yoseku" is input, a conversion result "prediction" is obtained by internal kana-kanji conversion, and the result is stored in the conversion result storage unit. 84.

When the conversion result is stored in the conversion result storage unit 84 by the internal kana-kanji conversion under the control of the second input prediction dictionary search processing unit 46, the second input prediction dictionary search processing unit 46 A search is made as to whether the conversion result stored in 84 matches the headline character string stored in the input prediction dictionary 86 (the headline character string) (step C8). If there is no such candidate, there is no input prediction candidate, and the process returns to step C3.

On the other hand, when the corresponding input prediction candidate is searched, the input prediction candidate (heading) is stored in the input prediction candidate storage section 88. The input prediction candidate display processing unit 34 causes the headings stored in the input prediction candidate storage unit 88 to be displayed as input prediction candidates (step C9).

When the input prediction candidate displayed here is selected by the user as a conversion result (step C1)
0), the reading provision processing unit 47 converts the input kana reading character string stored in the input character string storage unit 80, that is, the reading character string subjected to the internal kana-kanji conversion, into the internal kana-kanji character. It is stored as a reading of a heading in the input prediction dictionary 86 searched based on the result of the conversion (step C1).
1).

For example, as shown in FIG. 15B, as a result of searching the input prediction dictionary 86 based on a character string obtained by internal kana-kanji conversion with respect to the input reading character string, FIG. When an input prediction candidate as shown in (c), that is, an input prediction candidate (prediction phrase) having no registered reading information as shown in FIG. Is selected by the user, it is displayed instead of the input character string as shown in FIG.

[0111] Further, the reading assignment processing section 47 registers the reading in correspondence with the input prediction candidate (predicted phrase) for which no reading information is provided as shown in FIG. 16B. In the example shown in FIG. 16 (b), the kana-kanji conversion dictionary 82 associates the heading kanji with the corresponding reading as shown in FIG. It is assumed that the readings are associated with each other.

In this way, even from a determined document having no reading information, it is automatically registered in the input prediction dictionary 86 as an input prediction candidate (prediction phrase), and the newly registered input prediction candidate is input. A normal input prediction dictionary is displayed as an input prediction candidate for the reading character string, and when selected, the input reading character string is registered in association with the selected input prediction candidate. 86 can be used as the input prediction candidate.

Thereafter, since the pronunciation is registered, a search is performed by the input prediction dictionary search processing unit 32 based on the pronunciation, and a character string registered as a predicted word is obtained as an input prediction candidate.

By automatically obtaining the input prediction candidates in this manner, the input prediction candidates corresponding to the document created by the user are sequentially registered in the input prediction dictionary 86. In document creation, input prediction can be used efficiently, and the load on the user when creating documents can be reduced.

Next, a fourth embodiment will be described.

In the fourth embodiment, seamless candidates obtained by seamless input processing are included in conversion candidates obtained by kana-kanji conversion so that they can be selected by the next candidate operation.

FIG. 17 shows a control program 12a and a document creation control program 1 in the system configuration shown in FIG.
It is a block diagram showing the functional composition of the document creation device in a 4th embodiment realized by executing 2b.
The same components as those in FIG. 2 described in the first embodiment are denoted by the same reference numerals, and detailed description is omitted.

The seamless dictionary search processing unit 50 determines whether the result of the Kana-Kanji conversion processing by the Kana-Kanji conversion processing unit 30 for the input character string stored in the input character string storage unit 80 is invalid, or regardless of the validity of the Kana-Kanji conversion. ,
The seamless input dictionary 94 is searched based on the input character strings stored in the input character string storage unit 80 to search for seamless candidates, and stored in the seamless candidate storage unit 95.

The conversion result validity check processing unit 52 determines whether the result of the Kana-Kanji conversion by the Kana-Kanji conversion processing unit 30 is valid. For example, if the result of kana-kanji conversion is a compound word of a compound word, it is determined that the conversion result is not appropriate.

[0120] The seamless candidate display processing section 53 displays the search result by the seamless dictionary search processing section 50 stored in the seamless candidate storage section 95.

The candidate display processing section 54 incorporates the seamless candidates searched for by the seamless dictionary search processing section 50 into the conversion candidates obtained by the kana-kanji conversion processing by the kana-kanji conversion processing section 30 and displays them as the next candidates.

The candidate selection processing section 55 receives, via the input control processing section 22, a conversion result for the input read character string from the candidates displayed by the seamless candidate display processing section 53 or the candidate display processing section 54. Selection according to the instruction from the user.

Next, the operation of the fourth embodiment will be described with reference to FIG.
This will be described with reference to the flowchart shown in FIG.

First, a character string read by kana is stored in the input character string storage unit 80 (step D1), and execution of kana-kanji conversion is instructed via the input control processing unit 22 (step D2). The unit 30 performs Kana-Kanji conversion on the read character string stored in the input character string storage unit 80 while referring to the Kana-Kanji conversion dictionary 82, and stores the result in the conversion result storage unit 84. Here, when a corresponding heading is searched for from the plurality of kana-kanji conversion dictionaries 82 for the input reading character string, each is stored in the conversion result storage unit 84 as a conversion candidate.

The conversion result validity check processing unit 52 checks whether the conversion candidate stored in the conversion result storage unit 84 is valid as a conversion result, for example, whether it is a compound word of a compound word. (Step D3).

As a result, if it is determined that the kana-kanji conversion candidate is appropriate, the kana-kanji conversion processing section 30 displays the kana-kanji conversion candidate for the input read character string (step D4).

On the other hand, if it is determined that the kana-kanji conversion candidate is not appropriate, the seamless dictionary search processing unit 50
Searches the seamless input dictionary 94 based on the read character string stored in the input character string storage unit 80 (step D5).

As a result, when the corresponding seamless candidate can be searched (step D6), the seamless dictionary search processing unit 50 stores the candidate in the seamless candidate storage unit 95 and stores the candidate in the conversion result storage unit 84 in the kana-kanji conversion candidate. Additional registration is made (step D7). Candidate display processing unit 5
4 displays the conversion candidates stored in the conversion result storage unit 84.

Note that it is not always necessary to check the validity of the kana-kanji conversion candidate in step D3, and the seamless dictionary search processing unit 50 searches the seamless input dictionary 94 based on the reading character string input unconditionally. Then, a seamless candidate may be obtained. The validity check is performed in advance by setting the mode /
It may be set to not perform.

FIG. 19 shows a display example of kana-kanji conversion candidates for the input reading character string.

For example, when a character string is input in the kana input mode (kana shift), the English character string “Ru
When the character string of “po” is to be input, it is assumed that the character string of “Suna Sasera” has been input as shown in FIG. That is,
It is assumed that the keys operated to input the English character strings "R", "u", "p", and "o" have been operated by kana shift.
In this case, when the kana-kanji conversion is executed, for example, FIG.
A conversion candidate of “sand sand” as shown in FIG.

In the case of Roman character input, the English character string "R
When an attempt is made to input "upo", a character string of "ru" is input as shown in FIG. 19B, and when this character string is subjected to Kana-Kanji conversion, as shown in FIG. 19C. , A conversion candidate for “report” is obtained.

As shown in FIG. 19 (c), the conversion candidate of "sand sera" is a compound word of a compound word, and is determined to be invalid as a candidate for kana-kanji conversion. A seamless input process is executed for
As shown in (d), a seamless candidate “Rupo” is obtained. In the case where the process of step D3 described in the flowchart of FIG. 18 is not performed, that is, the seamless input process is executed unconditionally without checking the validity of the candidate obtained by the Kana-Kanji conversion, the same process as in FIG. As shown in FIG. 19 (d), the seamless candidate “Rupo”
Is obtained.

Note that the seamless input dictionary 94 includes FIG.
As shown in FIG. 0, it is assumed that the reading of kana input, the reading of Roman character input, and the respective character strings of the heading are registered in association with each other. By searching the seamless input dictionary 94 by the seamless dictionary search processing unit 50 (seamless input processing), a heading, such as “Rupo”, which is a character string of another character type different from the kana character corresponding to the input reading character string, is obtained. You can ask.

When a seamless candidate is obtained as shown in FIG. 19D and additionally registered as the next candidate for kana-kanji conversion, the input shown in FIG.
FIG. 19E shows the input shown in FIG.
As shown in (f), when the display of the next candidate is instructed, the character string of the heading stored in the seamless input dictionary 94, that is, “Rupo” is displayed.

As described above, the seamless candidate is included in the result of the Kana-Kanji conversion, and can be displayed and selected by the operation of the next candidate display. A conversion result can be selected, and even if a shift operation at the time of inputting has been performed by mistake and a reading character string has been input, it is not necessary to input the character string again, and the burden on the user can be reduced.

Next, a fifth embodiment will be described.

In the fifth embodiment, an input prediction process is executed based on an input character string including a wild card.

FIG. 21 shows a control program 12a and a document creation control program 1 in the system configuration shown in FIG.
It is a block diagram showing the functional composition of the document creation device in a 5th embodiment realized by executing 2b.
The same components as those in FIG. 2 described in the first embodiment are denoted by the same reference numerals, and detailed description is omitted.

The wild card search processing unit 60 searches whether or not a wild card (special character) is included in the input character string stored in the input character string storage unit 80.

The mode setting processing section 62 sets whether or not to execute the input prediction processing including a wild card, and stores the set contents in the mode setting information storage section 96.

When the mode setting processing unit 62 sets the mode setting information storage unit 96 to execute an input prediction process using a wild card, the wildcard assignment processing unit 65 stores the input character string storage unit 80 in the input character string storage unit 80. A wild card is assigned to the input character string so that a search process including the wild card is executed.

The candidate display processing section 66 displays input prediction candidates obtained by input prediction processing on a character string including a wild card.

Next, the operation of the fifth embodiment will be described with reference to FIG.
This will be described with reference to the flowchart shown in FIG.

First, when the input character string is stored in the input character string storage section 80, the wildcard search processing section 60 performs a wildcard, that is, an asterisk "*" or a question mark "?" It is checked whether special characters such as are included (step E1). The asterisk "*" and the question mark "?" Are special characters that represent any character or character string, with "*" indicating a character string of any length and "?" Indicating any one character. I do.

If there is no wild card (step E2), the wild card assigning unit 65 refers to the seamless candidate storage unit 95 to execute the input prediction process using the wild card, that is, even if the input character string partially matches. It is determined whether the setting for input prediction has been made (step E3).

If the input prediction is not set even if the input character strings partially match, the input prediction dictionary search processing unit 64
Searches the input prediction dictionary 86 for the input reading character string stored in the input character string storage unit 80, and determines whether there is an input prediction candidate for the reading character string (step E).
7).

If the input prediction candidate is not obtained, the process is terminated. If the input prediction candidate is obtained, the input prediction candidate is stored in the input prediction candidate storage section 88. In this case, the input prediction candidate display processing unit 34 displays the input prediction candidates stored in the input prediction candidate storage unit 88 (Step E8).

On the other hand, when the execution of the prediction processing using the wildcard is set, the wildcard providing processing unit 65 applies an asterisk before and after the input character string, that is, all the readings including the input reading character string. A wildcard "*" is added so that the corresponding headline is searched as a seamless candidate (step E5).

The input prediction dictionary search processing section 64 searches the input prediction candidate storage section 88 according to the wildcard included in the input character string (step E6). That is, the asterisk “*” may be any character string of one or more characters, and the question mark “?” Searches the input prediction candidate storage unit 88 as a search target for any one character. In addition, regarding the method of searching for a character string using a wildcard, it is assumed that an existing description is used.
Detailed description is omitted.

When such a candidate is obtained, it is displayed in the same manner as the input prediction candidate obtained by the normal input prediction processing.

FIG. 23 shows a specific example of an input prediction process using a wild card.

For example, as shown in FIG. 23 (a), when a hiragana character string “Naga no Orin Pok sosiki Iinkai” is input, the kana-to-kanji conversion is executed as shown in FIG.
As shown in (b), "Nagano Olympic Organizing Committee"
Is obtained. At this time, as shown in FIG. 23 (c), it is assumed that the input read character string has been registered as a new word in the input prediction candidate storage unit 88 with the input prediction dictionary 86 reading the kana-kanji conversion result as a heading. .

After that, when the read character string of “Nagano” is input, the input prediction dictionary search processor 64 searches the input prediction dictionary 86 for the input prediction candidate “Nagano Olympic Organizing Committee”. It is displayed as shown in FIG.

FIG. 23 shows an example in which a wild card is used.
As shown in (e), when a reading character string of “* inkai” is input, an input prediction candidate that includes “inkai” in the last character string in the heading of the input prediction dictionary 86 Is searched.

As a result, as shown in FIG. 23 (c), since the reading "Naga no Orin Pak sosikiinkai" is registered, the heading "Nagano Olympic Organizing Committee" corresponding to this reading is registered. Is retrieved and displayed as shown in FIG.

Even if no wildcard is added to the input character string, if the mode setting processing section 62 has set “predict even partial match”, the internal Is added to the input character string, and based on this character string, the input prediction dictionary 8
23, the input prediction candidate “Nagano Olympic Organizing Committee” is displayed as shown in FIG. 23 (f), as in the case shown in FIG. 23 (e).

As described above, by enabling the input prediction processing using the wild card, the input prediction processing can be more effectively utilized, and the burden on the user when creating a document can be reduced.

In the above description, only the case of "predict even a partial match" is described by the mode setting. However, a plurality of modes that can be specified by a combination of wildcards can be arbitrarily provided and set. Is also good.

Next, a sixth embodiment will be described.

The sixth embodiment makes it possible to simultaneously display seamless candidates and input prediction candidates for an input character string, even if the user erroneously shifts the character input state and inputs a character.

FIG. 24 shows a control program 12a and a document creation control program 1 in the system configuration shown in FIG.
FIG. 14 is a block diagram illustrating a functional configuration of a document creation device according to a sixth embodiment, which is realized by executing 2b.
The same components as those in FIG. 2 described in the first embodiment are denoted by the same reference numerals, and detailed description is omitted.

The input prediction dictionary search processing section 67 searches the input prediction dictionary 86 based on the character string obtained by the seamless input dictionary search processing section 68, and is inputted following the input character string up to the present. An input prediction candidate that is a character string having a high possibility is obtained.

The seamless input dictionary search processing section 68 searches the seamless input dictionary based on the input reading character string, and uses another character type different from the kana character corresponding to the input reading character string. Find a heading that is a string.

The candidate display processing section 69 compares the character string obtained by the seamless input dictionary search processing section 68 with the character string searched by the input prediction dictionary search processing section 67.
Display as a conversion candidate for the input reading character string.

The candidate selection processing unit 70
9, a character string to be a conversion result for the input read character string is selected in accordance with an instruction from the user input through the input control processing unit 22.

In the seamless input dictionary 94, a heading which is a character string of another character type different from the kana character and a reading character string of a kana character corresponding to the heading are registered in association with each other.

Next, the operation of the sixth embodiment will be described with reference to FIG.
This will be described with reference to the flowchart shown in FIG.

When the input character string is stored in the input character string storage unit 80, the seamless input dictionary search processing unit 6
8 searches the seamless input dictionary 94 based on the input read character string, and determines whether or not there is a corresponding seamless input process (step F1).

If the corresponding seamless candidate is obtained (step F2), the seamless input dictionary search processing section 68
Is stored in the seamless candidate storage unit 95 (display candidate memory).

Further, based on the seamless candidates obtained by searching the seamless input dictionary 94 by the seamless input dictionary search processing section 68, the input predictive dictionary search processing section 67 performs an input corresponding to the head of the input predictive dictionary 86 corresponding to the forward match. It is determined whether or not there is a prediction candidate (step F4).

If there is a corresponding input prediction candidate,
The input prediction dictionary search processing unit 67 stores the input prediction candidates in the input prediction candidate storage unit 88 (display candidate memory).
The candidate selection processing unit 70 displays a list of the seamless candidates and the input prediction candidates stored in the seamless candidate storage unit 95 and the input prediction candidate storage unit 88, that is, the display candidate memory.

FIG. 26 shows an example in which candidates obtained for the input character string are displayed in a list. The input prediction dictionary 86 and the seamless input dictionary 94
It is assumed that each stores information as shown in FIG.

First, as shown in FIG. 26 (a), when the hiragana character string "tontokaimo" is input, the seamless input dictionary 94 is searched by the seamless processing.
The character string of the seamless candidate "system" is obtained.
Further, based on the character string of the seamless candidate “system”, the input prediction processing is executed to search the input prediction dictionary 86, and as a result, the reading “system manager” is obtained.
Therefore, a heading (input prediction candidate) corresponding to the reading and “system manager” are searched. As a result, as shown in FIG. 26 (c), a list of seamless candidates and input prediction candidates is displayed simultaneously.

Similarly, when the reading character string “miite” is input, the alphabet “n” is regarded as a seamless candidate.
ew ", and the seamless candidate" ne
As a result of searching the input prediction dictionary 86 based on “w”, a character string of the input prediction candidate “New York” is obtained.

In this way, not only the seamless processing is performed on the input character string, but also the input prediction processing is executed based on the seamless candidates, so that the seamless candidates and the input prediction candidates are simultaneously made. The conversion result can be arbitrarily selected. Therefore, the seamless input processing and the input prediction processing are made totally efficient, and the burden on the user when creating a document can be reduced.

Next, a seventh embodiment will be described.

In the seventh embodiment, when the same input prediction candidate is continuously displayed a predetermined number of times for a read character string sequentially input one by one and is not selected, the input prediction candidate is an unnecessary input prediction candidate. Automatically erase as

FIG. 28 shows a control program 12a and a document creation control program 1 in the system configuration shown in FIG.
It is a block diagram showing the functional composition of the document creation device in a 7th embodiment realized by performing 2b.
The same components as those in FIG. 2 described in the first embodiment are denoted by the same reference numerals, and detailed description is omitted.

The display candidate initialization processing unit 73 deletes the input prediction candidates stored in the input prediction candidate storage unit 88 based on the number of candidate displays counted by the same control counter control processing unit 74.

The same control counter control processing section 74 causes the input prediction candidate comparison processing section 75 to input the input prediction candidates previously stored in the input prediction candidate storage section 88 and the input reading character string obtained by the input read character string. When it is determined that the prediction candidates are the same, the candidate display count for the input prediction candidate is counted in the candidate display count storage unit 99.

The input prediction candidate comparison processing unit 75 stores the input prediction candidates corresponding to the read character strings input up to now obtained by the input prediction dictionary search processing unit 32 and the input prediction candidate storage unit 88 first. Then, it is determined whether the input prediction candidates are the same by comparing the input prediction candidates.

The candidate display count setting processing unit 76 sets the candidate display count when deleting the input prediction candidate stored in the input prediction candidate storage unit 88 by the display candidate initialization processing unit 73.
In accordance with an instruction from the user, the candidate display count storage unit 9 is set in advance.
Set to 9.

The same control counter 98 is a counter for storing the number of candidate displays counted by the same control counter control processing unit 74 for each input prediction candidate stored in the input prediction candidate storage unit 88.

The candidate display count storage unit 99 stores the candidate display counts of the input prediction candidates stored in the input prediction candidate storage unit 88 until they are deleted by the display candidate initialization processing unit 73. Stored by

Next, the operation of the seventh embodiment will be described with reference to FIG.
This will be described with reference to the flowchart shown in FIG.

First, as initialization processing, the display candidate initialization processing section 73 initializes the input prediction candidate storage section 88 (display candidate memory) (step G1), and the same control counter control processing section 74 sets the same control counter 98. Is initialized (step G2).

When the input character string storage unit 80 stores the input character string, the input prediction dictionary search processing unit 32
The input prediction dictionary 86 is searched based on the read character string, and a corresponding input prediction candidate is searched (step G3). Here, when the corresponding input prediction candidate is obtained, the input prediction candidate comparison processing unit 75 compares the input prediction candidate searched by the input prediction dictionary search processing unit 32 with the input prediction candidate stored earlier. By comparison, it is determined whether the character strings are the same (step G5).

At this time, if the input prediction candidate comparison processing section 75 determines that the character strings are the same, the searched input prediction candidates are stored in the input prediction candidate storage section 88 (display candidate memory) ( Step G9). The input prediction candidates stored in the input prediction candidate storage unit 88 are displayed as input prediction candidates for the read character string input by the input prediction candidate display processing unit 34 (Step G10).

On the other hand, when it is determined that the input prediction candidate retrieved by the input prediction candidate comparison processing section 75 is the same as the input prediction candidate previously stored in the input prediction candidate storage section 88, If the read character string input up to that time is already displayed as an input prediction candidate, the same control counter control processing unit 74 adds 1 to the number of display candidates for this input prediction candidate and performs the same control. It is stored in the counter 98 (step G6).

Here, the display candidate initialization processing unit 73 determines that the value of the candidate display count stored in the same control counter 98 is
It is determined whether or not a value set in the candidate display count storage unit 99, that is, a threshold set in advance or a value set by the user is exceeded (step G7). If the value of the candidate display count stored in the same control counter 98 does not exceed the value set in the candidate display count storage unit 99, the display candidate initialization processing unit 73 does nothing. Therefore, the input prediction candidate display processing unit 34 displays the contents of the input prediction candidates stored in the input prediction candidate storage unit 88, that is, the input prediction candidates obtained by the read character strings input up to now (step G10). ).

Hereinafter, every time a reading character string is sequentially input,
The above-described processing is repeated. In other words, each time a reading character string is input one character at a time, an input prediction candidate is searched for and displayed. If the same input prediction candidate as the previously searched input prediction candidate is searched, the input prediction candidate is searched for. The value of the candidate display count for the input prediction candidate is updated and stored in the same control counter 98.

The display candidate initialization processing unit 73 monitors the number of candidate displays counted by the same control counter 98, and when the counted value exceeds the value stored in the candidate display number storage unit 99, The corresponding input prediction candidate stored in the input prediction candidate storage unit 88 is deleted. Further, the same control counter control processing unit 74 initializes the number of candidate displays counted by the same control counter 98 corresponding to the input prediction candidate (step G8).

As a result, candidates that have been displayed a predetermined number of times consecutively are no longer displayed by the input prediction candidate display processing unit 34.

FIG. 30 shows a display example of input prediction candidates each time a read character string is sequentially input.

First, as shown in FIG. 30 (a), it is assumed that, when a reading character string "kisha" is input, two input prediction candidates are searched and displayed in a list.

It is assumed that the candidate display count storage unit 99 has set the threshold for the candidate display count to “2” by the candidate display count setting processing unit 76. That is, it is assumed that the input prediction character string is set so that the input prediction candidate is not displayed continuously more than three times (input of three character reading characters).

Here, when the reading "ma" is input after the previously input reading character string "kisha", FIG.
As shown in (b), it is assumed that the same input prediction candidates as in FIG. 30 (a) are obtained and displayed in a list. In this case, the number of display times of each of the two input prediction candidates is incremented by one in the same control counter 98.

Further, when the reading “su” is successively input, the same input prediction candidate as shown in FIG. Is searched and displayed. In this case, the same control counter 98 adds 1 to the number of display times of each of the two input prediction candidates.

Next, when the reading "ma" is input, the same input prediction candidate as that shown in FIG. 30 (c) is searched for the reading character string "kisha masama" that has been input so far. Since the value of the candidate display count for the two input prediction candidates becomes “3” and exceeds the value set in the same control counter 98, the display candidate initialization processing unit 73 initializes the number of display times, and FIG. ), It is not displayed as an input prediction candidate.

As described above, as to the input prediction candidates which are continuously displayed a predetermined number of times as the reading character string is sequentially input, the user does not want to input the undesired input as a conversion result for the input reading character string. Automatically deletes it as a prediction candidate. This eliminates the need for the user to check undesired input prediction candidates displayed in a list, thereby reducing the work load.

Note that the method described in the above-described embodiment includes, as programs that can be executed by a computer, for example, a magnetic disk (floppy disk, hard disk, etc.), an optical disk (CD-ROM,
DVD and the like, and can be written to a recording medium such as a semiconductor memory and provided to various devices. Further, it is also possible to transmit the data via a communication medium and provide it to various devices. A computer that implements the present apparatus reads the program recorded on a recording medium or receives the program via a communication medium, and executes the above-described processing by controlling the operation of the program.

[0203]

As described above in detail, according to the present invention, it is possible to reduce the load on the user and to provide effective input support.

[Brief description of the drawings]

FIG. 1 is a block diagram showing the system configuration of a document creation device according to an embodiment.

FIG. 2 is a block diagram illustrating a functional configuration of the document creation device according to the first embodiment.

FIG. 3 is a flowchart for explaining the operation of the document creation device according to the first embodiment.

FIG. 4 is a diagram showing an example of information stored in an input prediction dictionary 86.

FIG. 5 is a view showing an example of display of input prediction candidates in the first embodiment.

FIG. 6 is a view showing an example of display of input prediction candidates in the first embodiment.

FIG. 7 is a block diagram illustrating a functional configuration of a document creation device according to a second embodiment.

FIG. 8 is a flowchart for explaining the operation of the document creation device according to the second embodiment.

FIG. 9 is a diagram showing an example of information stored in a kana-kanji conversion dictionary 82.

FIG. 10 is a diagram showing an example of information stored in a character positional relationship table 90 by a character positional relationship storage processing unit 40.

FIG. 11 is a diagram showing a state of editing a character string obtained by kana-kanji conversion.

FIG. 12 is a diagram showing an example of reading and heading information automatically registered in an input prediction dictionary 86.

FIG. 13 is a block diagram illustrating a functional configuration of a document creation device according to a third embodiment.

FIG. 14 is a flowchart for explaining the operation of the document creation device according to the third embodiment.

FIG. 15 is a diagram showing the progress of processing when information is registered in the input prediction dictionary 86.

FIG. 16 is a diagram showing contents of information stored in an input prediction dictionary 86.

FIG. 17 is a block diagram illustrating a functional configuration of a document creation device according to a fourth embodiment.

FIG. 18 is a flowchart for explaining the operation of the document creation device according to the fourth embodiment.

FIG. 19 is a diagram showing a display example of kana-kanji conversion candidates for an input reading character string.

FIG. 20 is a diagram showing an example of information stored in a seamless input dictionary 94.

FIG. 21 is a block diagram illustrating a functional configuration of a document creation device according to a fifth embodiment.

FIG. 22 is a flowchart for explaining the operation of the document creation device according to the fifth embodiment.

FIG. 23 is a diagram showing a specific example of an input prediction process using a wild card.

FIG. 24 is a block diagram illustrating a functional configuration of a document creation device according to a sixth embodiment.

FIG. 25 is a flowchart for explaining the operation of the document creation device according to the sixth embodiment.

FIG. 26 is a diagram showing an example in which candidates obtained for an input character string are displayed in a list.

FIG. 27 shows an input prediction dictionary 86 and a seamless input dictionary 94
The figure which shows an example of the information stored in.

FIG. 28 is a block diagram illustrating a functional configuration of a document creation device according to a seventh embodiment.

FIG. 29 is a flowchart for explaining the operation of the document creation device according to the seventh embodiment.

FIG. 30 is a diagram showing a display example of input prediction candidates each time a reading character string is sequentially input.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 10 ... CPU 12 ... Memory 12a ... Control program 12b ... Document creation control program 12c ... Document information part 12d ... Information storage part 14 ... Input device 16 ... Display device 18 ... Storage device 18a ... Information storage part 18b ... Program 22 ... Input control Processing unit 24 Output control processing unit 26 Document creation control unit 28 Information storage unit 30 Kana-Kanji conversion processing unit 32 Input prediction dictionary search processing unit 34 Input prediction candidate display processing unit 35 Input prediction candidate selection processing unit 36 ... Same character string check processing unit 37 ... Display confirmation position control processing unit 38 ... Input prediction candidate integration processing unit 40 ... Character positional relationship storage processing unit 41 ... Character positional relationship update processing unit 42 ... Character editing processing unit 43 ... Input prediction candidate Registration processing unit 45 ... Internal kana-kanji conversion control processing unit 46 ... Second input prediction dictionary search processing unit 47 ... Reading provision processing unit 48 ... Predicted phrase automatic registration processing unit 50 ... Seamless dictionary search processing unit 52 ... Conversion result validity check processing unit 53 ... Seamless candidate display processing unit 54 ... Candidate display processing unit 55 ... Candidate selection processing unit 60 ... Wildcard search processing unit 62: Mode setting processing unit 64: Input prediction dictionary search processing unit 65: Wildcard provision processing unit 66: Candidate display processing unit 67: Input prediction dictionary search processing unit 68: Seamless input dictionary search processing unit 69: Candidate display processing unit 70 ... Candidate selection processing unit 73 Display candidate initialization processing unit 74 Same control counter control processing unit 75 Input prediction candidate comparison processing unit 76 Candidate display count setting processing unit 80 Input character string storage unit 82 Kana-Kanji conversion dictionary 84 ... conversion result storage unit 86 ... input prediction dictionary 88 ... input prediction candidate storage unit 90 ... character positional relationship table 91 ... Conversion result storage unit 94 ... seamless input dictionary 95 ... seamless candidate storage unit 96 ... mode setting information storage unit 98 ... same control counter 99 ... candidate impressions storage unit

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Tomoko Kudo 2-9-9 Suehirocho, Ome City, Tokyo Inside the Toshiba Ome Plant (72) Inventor Hideto Izawa 2-9-9 Suehirocho, Ome City, Tokyo Stock F-term in Toshiba Ome Plant (reference) 5B009 KA04 MA05 MA08 MA09 MA11 ME15 ME21 MF03 MF05 MH02 MH04 MJ00 RB31

Claims (9)

[Claims] 1. A document preparation apparatus for converting an input reading character string into another character string related to the reading character string and inputting the input reading character string in addition to character input by kana-kanji conversion means of a kana-kanji conversion means. It is referred to when executing processing, and based on an input prediction dictionary in which a reading character string is registered in correspondence with a character string of an input prediction candidate as an input prediction result, and an input reading character string, An input prediction dictionary search processing unit that searches the input prediction dictionary and obtains an input prediction candidate that is a character string that is likely to be input following the input character string up to the present; and a search performed by the dictionary search processing unit. The same character string check processing means for checking whether or not each character string of the input prediction candidate has a character string part that matches another character string; Input prediction candidate integration processing means for integrating a character string of an input prediction candidate determined to have a character string portion matching a column into a simplified character string; and simplification integrated by the input prediction candidate integration processing means. Input prediction candidate display processing means for displaying the input character string and the character string of the input prediction candidate which are not integrated, and converting the character string displayed by the input prediction candidate display processing means into the input reading character string A document selection device comprising: candidate selection processing means for selecting a resulting character string. 2. A document creation apparatus for inputting a read character string by converting the input read character string into another character string related to the read character string, in addition to the character input by the kana-kanji conversion means of the kana-kanji conversion means. It is referred to when executing processing, and based on an input prediction dictionary in which a reading character string is registered in correspondence with a character string of an input prediction candidate as an input prediction result, and an input reading character string, An input prediction dictionary search processing unit that searches the input prediction dictionary and obtains an input prediction candidate that is a character string likely to be input subsequent to the input character string up to the present time; A character position relation storage processing means for storing a conversion result character string obtained by the kana-kanji conversion means in association with a reading corresponding to each character of the conversion result character string; and a character position relation storage processing means. Character editing processing means for editing the stored conversion result character string, and, according to the contents of the editing by the character editing processing means, the input read character string stored by the character position relation storage processing and A character position relation update processing means for updating the conversion result character string obtained by the kana-kanji conversion means; and a read character string and a conversion result character string stored by the character position relation storage processing means, A document creation device comprising: input prediction candidate registration processing means for registering a reading character string and an input prediction candidate in association with each other. 3. A document preparation apparatus for converting a read character string into another character string related to the read character string and inputting the character string in addition to character input by kana-kanji conversion by a kana-kanji conversion means. It is referred to when executing processing, and based on an input prediction dictionary in which a reading character string is registered in correspondence with a character string of an input prediction candidate as an input prediction result, and an input reading character string, An input prediction dictionary search processing unit that searches the input prediction dictionary to obtain an input prediction candidate that is a character string that is likely to be input following the input character string up to the present time; Predicted word automatic registration processing means for registering a conversion result character string as a character string of an input prediction candidate of the input prediction dictionary in a predetermined character string unit, and kana-kanji conversion means for an input reading character string Therefore, an internal kana-kanji conversion control processing means for internally executing kana-kanji conversion, and based on the character string obtained by the kana-kanji conversion of the internal kana-kanji conversion control processing means, search the input prediction dictionary to find an input prediction candidate. A second input prediction dictionary search processing means to be obtained; an input prediction candidate display processing means for displaying a character string of an input prediction candidate searched by the input prediction dictionary search processing means and the second input prediction dictionary search processing means; Candidate selection processing means for selecting, from the character strings displayed by the prediction candidate display processing means, a character string to be a conversion result for the input reading character string; and a character string of the input prediction candidate selected by the candidate selection processing means Is a character string registered by the predicted phrase automatic registration processing means, the character string stored in the input prediction dictionary Against, the document creating apparatus characterized by comprising a read grant processing means for storing in association with strings readings were subject to internal kanji conversion by the internal kana-kanji conversion control processing means. 4. A document creating apparatus for converting an input reading character string into another character string related to the reading character string and inputting the converted character string, wherein the reading character string and a character string of a headword as a conversion result are used. Kana-Kanji conversion processing means for searching the Kana-Kanji conversion dictionary registered in association with the registered kana-kanji conversion dictionary and obtaining a character string of a headword as a conversion candidate based on the input reading character string; A seamless input dictionary in which a heading, which is a character string of another character type different from the heading, and a reading character string of a kana character corresponding to the heading are registered in association with each other; Search the seamless input dictionary to find a heading that is a character string with another character type different from the kana character corresponding to the input reading character string,
A document creation apparatus comprising: a seamless dictionary search processing means for adding to the conversion candidates obtained by the kana-kanji conversion processing means. 5. A conversion result validity determining means for determining validity of a character string as a conversion candidate obtained by the kana-kanji conversion processing means, wherein the seamless dictionary search processing means comprises the conversion result validity determination. 5. The document creation apparatus according to claim 4, wherein when the means determines that the character string to be a conversion candidate is not valid as a conversion result, the seamless input dictionary is searched. 6. A document creation apparatus for converting an input reading character string into another character string related to the reading character string and inputting the converted character string, which is referred to when executing an input prediction process. An input prediction dictionary in which a character string is registered in correspondence with a character string of an input prediction candidate as an input prediction result, and an input character string contains an arbitrary character or a special character representing a character string. Search processing means for searching whether or not there is, and when the special character is searched by the search processing means, searches the input prediction dictionary based on the searched special character and the input read character string An input prediction dictionary search processing means for obtaining an input prediction candidate which is a character string which is likely to be input following the input character string up to the present. 7. As a condition for a search for the input prediction dictionary by the input prediction dictionary search processing means, the search corresponds to a case where a reading character string registered in the input prediction dictionary includes an input reading character string. Setting means for arbitrarily setting a mode designation indicating that, if the special character has not been searched by the search processing means, if the mode designation has been set by the setting means, the input character string And an input predictive dictionary search processing means, wherein the input predictive dictionary search processing means converts the input predictive dictionary based on a read character string to which the special character has been added by the assigning means. 7. The document creation apparatus according to claim 6, wherein a search is performed. 8. A kana-kanji conversion method for converting a kana-kanji character into a character string related to the kana-kanji conversion means and converting the input character string into another character string. A seamless input dictionary in which a heading, which is a character string of another character type different from the heading, and a reading character string of a kana character corresponding to the heading are registered in association with each other; It is referred to when performing a seamless dictionary search processing and a seamless dictionary search processing means for searching for a heading which is a character string of another character type different from the kana character corresponding to the input reading character string and an input prediction processing. An input prediction dictionary in which a read character string and a character string of an input prediction candidate as an input prediction result are registered in association with each other; Input prediction dictionary search processing means for searching the input prediction dictionary based on the input character string, and obtaining an input prediction candidate that is a character string that is likely to be input following the input character string up to the present time; Candidate display processing means for displaying the character string obtained by the seamless dictionary search processing means and the character string searched by the input predictive dictionary search processing means as conversion candidates for the input read character string; A document creation device characterized by the following. 9. A document creation apparatus for converting an input reading character string into another character string related to the reading character string and inputting the converted character string, which is referred to when executing an input prediction process, and An input prediction dictionary in which a character string and an input prediction candidate character string as an input prediction result are registered in association with each other, and the input prediction dictionary is searched based on the input read character string, and the input prediction to date is performed. Input prediction dictionary search processing means for obtaining an input prediction candidate that is a character string likely to be input following the character string; and an input corresponding to the current input character string obtained by the input prediction dictionary search processing means Candidate storage means for storing prediction candidates, based on the character strings stored in the candidate storage means, input prediction candidate display processing means for displaying the input prediction candidates corresponding to the input character string up to now, The input Input prediction candidate comparison processing means for determining whether the input prediction candidate obtained by the measurement dictionary search processing means is the same as the input prediction candidate previously stored in the candidate storage means, and the input prediction candidate comparison processing means Counting means for counting the number of times that the input prediction candidates are determined to be the same, and a candidate for erasing the input prediction candidates stored in the candidate storage means when the number of times counted by the counting means has reached a predetermined value. A document creation device comprising: an initialization processing unit.