JP2024172025A - Information processing device, information processing method, and program - Google Patents

Abstract

An information processing apparatus, an information processing method, and a program are provided that can reduce the effort required for a user to classify electronic document data.
The information processing device includes a processing unit that performs processing to generate a target string based on lines extracted line by line from an electronic document, compares the generated target string with a predetermined string, and outputs a candidate classification destination for the electronic document based on a comparison result. If the extracted line contains spaces, the processing unit deletes the spaces from the line to generate the target string.
[Selected figure] Figure 2

Description

This invention relates to an information processing device, an information processing method, and a program.

Conventionally, technology is known that recognizes characters from an image and obtains classification items (Patent Document 1). In addition, Patent Document 2 discloses technology that appropriately reads highlighting that was made in the original document from character strings recognized from the image data of the document.

On the other hand, many transactions are now being conducted using electronic documents. Electronic documents are quickly exchanged over networks. PDF (Portable Document Format) is widely used as a format for electronic documents.

JP 2008-176625 A JP 2017-126270 A

The data of electronic documents received via the network is classified, processed, and stored by the person in charge. However, as the volume of electronic documents increases, the amount of work required by the person in charge for classification also increases, which is an issue.

The object of the present invention is to provide an information processing device, information processing method, and program that can reduce the effort required for a person in charge to classify electronic document data.

In order to achieve the above object, the present invention provides
a storage unit that stores the content detected from the electronic document;
a processing unit that performs a process of detecting a character string corresponding to the content from a text obtained by extracting and arranging characters included in an electronic document in order, and outputting a classification corresponding to the character string;
The information processing device includes:

The present invention has the advantage of reducing the effort required for personnel to classify electronic document data.

1 is a block diagram showing a functional configuration of an information processing apparatus according to an embodiment of the present invention; FIG. 1 is a diagram illustrating a flow of document classification in an information processing device. FIG. 2 is a diagram illustrating classification definition data. FIG. 13 is a diagram showing an example of the beginning portion of an electronic ledger document. 4 is a flowchart showing a control procedure of a monitoring control process. 13 is a flowchart showing a control procedure of a document classification control process executed by a registration tool.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
FIG. 1 is a block diagram showing the functional configuration of an information processing device 1 according to the present embodiment.

The information processing device 1 may be a normal PC (Personal Computer). The information processing device 1 includes a CPU 11 (Central Processing Unit) (control unit), a RAM 12 (Random Access Memory), a storage unit 13, a display unit 14, an operation reception unit 15, a communication unit 16, etc.

The CPU 11 is a processor that performs arithmetic processing. There may be a single CPU 11, or multiple CPUs operating in parallel, or each operating independently depending on the application. The CPU 11 may be not only a general-purpose processor, but also a microcomputer or an ASIC (Application Specific Integrated Circuit). The CPU 11, as a processing unit, classifies and stores electronic documents acquired by the information processing device 1.

RAM 12 provides working memory space for CPU 11 and stores temporary data.

The storage unit 13 includes a non-volatile memory. The non-volatile memory is, for example, a flash memory or a hard disk drive (HDD). Various programs and setting data are stored in the non-volatile memory. The storage unit 13 also stores a document database 134. The various programs include an email software 131 and a program 132 for document classification including a monitoring tool and a registration tool described below. The setting data includes classification definition data 135 that defines the contents to be detected from an electronic document and used to classify the electronic document. The download data 133 is data acquired from outside and stored in a download folder (or directory). This data includes, for example, data attached to a received email and data downloaded from an external website or the like via HTTP. The download folder may have a different name.

The display unit 14 has a digital display screen and displays various information on the digital display screen based on the control of the CPU 11. The digital display screen is, for example, a liquid crystal display (LCD) or an organic EL (Electro-Luminescent) display.

The operation reception unit 15 receives an input operation from an external source such as a user. The operation reception unit 15 outputs an operation signal corresponding to the received input operation to the CPU 11. The operation reception unit 15 may include, for example, a keyboard and a pointing device. The pointing device may include a mouse. The operation reception unit 15 may also have a touch panel that is positioned so as to overlap the digital display screen.
The information processing device 1 does not necessarily have to have the display unit 14 and the operation reception unit 15. These may be externally attached to the information processing device 1 as peripheral devices via a connection terminal such as a USB (Universal Serial Bus) terminal or a PS/2 terminal. Alternatively, these may be external devices and communicatively connected to the information processing device 1 via the communication unit 16.

The communication unit 16 controls communication with an external device according to a predetermined protocol. The predetermined protocol may include, for example, TCP/IP in a LAN (Local Area Network). The communication unit 16 may have a network card for controlling wireless communication such as Bluetooth (registered trademark) or WiFi. The communication unit 16 may be capable of communicating with an external device according to each communication protocol. The external device may include the configuration of the display unit 14 and the operation reception unit 15 as described above.
The computer of this embodiment includes at least a CPU 11 and a RAM 12, and may also include a storage unit 13 and a communication unit 16. Furthermore, the entire information processing device 1 of this embodiment may correspond to a computer.

Next, a document classification process performed by the information processing device 1 of this embodiment will be described.
FIG. 2 is a diagram illustrating a flow of document classification in the information processing device 1. As shown in FIG.

In the information processing device 1, electronic document data related to the electronic ledger is classified and registered in the document database 134. The format of the electronic document to be classified is a PDF file. When the electronic document is stored or saved in a specific folder or directory (a predetermined location), for example, a download folder, the monitoring tool detects the addition of the electronic document. In other words, the monitoring tool may be a resident program. When the monitoring tool detects the addition of an electronic document, it launches the registration tool.

The registration tool analyzes the added PDF file. The registration tool obtains text data obtained by extracting text (displayed characters, including numbers, symbols, signs, etc.) from the PDF file (electronic document) one line at a time as the target character string. If the PDF file is tagged data, the registration tool performs structural analysis on the PDF file to extract the entire text of the displayed content. The registration tool identifies positions that indicate line breaks in the text and divides the text into one line (line) at the positions. When dividing into lines, the registration tool may delete control codes or tags that indicate line breaks. In addition, when extracting the entire text or dividing into lines, the registration tool may delete or ignore line breaks in data that are not related to line breaks in the display in the target character string. Furthermore, the registration tool may identify display settings such as font size, font type, and font color from tag data corresponding to the text extracted at this time. The registration tool compares the extracted text (target character string) of each line with the classification definition data 135, and searches for a keyword (predetermined character string) that is the detection content defined by the classification definition data 135. The registration tool extracts classification destination candidates according to the detected content (character string), and displays (outputs) the candidates on the display unit 14. When the operation reception unit 15 receives an input operation related to selection from among these candidates, the classification destination is determined according to the input operation, and the PDF file is registered in the document database 134 together with the classification information.

Note that files other than the electronic document data to be registered may be stored in the download folder. If a file other than a PDF format is added, the monitoring tool will not start the registration tool. Even if a PDF format file is added and the registration tool is started, the user can select not to register this file. In this case, the PDF file is left in the download folder as is and can be used for any other purpose.

The monitoring tool may also monitor new files that are added to a set folder (set location) other than the download folder. PDF files related to electronic ledgers are temporarily stored in a dedicated folder that is different from other files, so that the registration tool is launched only when a file that requires classification is stored.

In addition, the entire display content of a PDF file, including the text portion, may be image data. In this case, the registration tool may determine that it is not electronic ledger data. Alternatively, the registration tool may use well-known character recognition technology to read text from the image. In this case, the registration tool may read the font size, font type, and font color of each character along with the text content.

FIG. 3 is a diagram for explaining the classification definition data 135. As shown in FIG.
As shown in FIG. 3A, the classification items (keys) may include document types according to the titles of electronic documents. Titles such as "quotation", "invoice", and "order form" may be character strings (keywords) that directly indicate classification types related to the document division types (keys) of electronic documents. Since titles are often located at the beginning of a document, these character strings may be searched for preferentially near the beginning of the document. Alternatively, these character strings may be searched for in a predetermined number of lines from the beginning of the document, for example, only three lines from the first line to the third line. In addition, when the display settings are acquired by structural analysis as described above, character strings may be searched for preferentially or selectively in a specific display setting, for example, in a line with a larger font size than other parts.

Furthermore, such titles often have spaces (blank spaces, full-width or half-width, any number of spaces; also includes spaces created by tabs or spaces where the positions of characters on either side of the spaces are specified separately by tags) inserted between each character. The registration tool removes these spaces from the extracted text (all at once or line by line) to identify (generate) the target string in which the detection content will be searched for (target string). If there are no spaces in the text, the text of the line can be used as is as the target string. By dividing the text into lines, characters from multiple lines are not unnecessarily joined together in the target string.

Although "purchase order" and "purchase order" have different titles, they are the same type of document. Therefore, in this case, they are listed on the same line, separated by a comma, in the classification definition data 135, and are therefore classified as being in the same category.

As shown in FIG. 3B, classification may also be performed according to the type of business partner, such as the destination from the company (organization) of the document or the sender to the company (organization). That is, the business partner type may be the classification item (key), and the name of the corporation representing the destination or sender may be the classification keyword. The destination is often located at the top of the document, but is not limited to the beginning. The information processing device 1 (registration tool) detects a character string (keyword) including the type of corporation that is often included in the destination from the extracted text. The type of corporation is, for example, a joint stock company, a limited liability company, a limited partnership company, a mutual company, a limited liability company, etc., and may often be abbreviated in parentheses such as "(stock)". The registration tool searches for destination candidates by setting these character string candidates in advance using regular expressions. In addition, "Dear", "Mr.", "Destination", "Sender", etc. in the same line as the character string of the destination candidate are not usually the name of the business partner. Therefore, these may be set in advance as terms (exclusion words) to be excluded from the character string representing the candidate type of corporation, or as terms indicating the beginning or end of the candidate. The user may be able to add a corporate type that has not been pre-defined to the classification definition data 135.

In cases where a business partner is often not a profit-making company, as shown in FIG. 3(c), a setting may be made in which names containing "corporation" are set as the type of corporation to be detected. In this case, the types of corporations may include, for example, incorporated associations, incorporated foundations, non-profit organizations (NPOs), school corporations, medical corporations, independent administrative organizations, and social welfare corporations.

Furthermore, as shown in FIG. 3(d), in cases where there is a strong relationship to law or accounting, for example, a regular expression capable of searching for law firms, tax accountant firms, patent attorney firms, judicial scrivener firms, administrative scrivener firms, law offices, legal offices, accounting offices, tax accountant offices, judicial scrivener offices, administrative scrivener offices, etc. can be set in the classification definition data 135. In addition, the information processing device 1 may have all the settings in FIG. 3(b) to FIG. 3(d), and only those necessary for the user may be selectively used. In addition, in cases where there is a lot of business with countries outside Japan, for example, LLC, Co. Ltd., Inc., etc. may be set in the classification definition data 135.

In a search for a string using such a regular expression, not only the business partner but also the company name of the company (organization) is likely to be detected. The registration tool may hold an exclusion list that compiles the excluded targets, such as the company itself, intermediaries, and financial institutions to be excluded from selection. Among the detected corporations, the excluded targets included in the exclusion list are lowered in priority as candidates for the classification type. Alternatively, the excluded targets may be completely excluded from the candidates for the classification type. Conversely, a corporate name once selected as a classification from the classification destination candidates may be registered in the classification list and displayed by the display unit 14 as a classification destination candidate with priority from the next time onwards. Note that if the target string contains both an excluded target and a prioritized classification destination candidate at the same time, it may be determined that the target string is not the text of a line that describes the classification destination candidate. In this case, regardless of the presence or absence of a keyword, the entire target string containing the excluded target may be excluded from the detection target for the classification destination candidate. Alternatively, only the terms of the classification destination candidate detected in the target string may be output, or the target string with the lowered priority as described above may be set as the classification destination string.

In particular, with long corporate names, the destination name may be written across multiple lines. For example, if only the searched word is written on one line and the remaining proper name is on another line, the registration tool can merge the lines before and after the line containing the searched word. Also, for example, if a match with part of a corporate name already registered in a classification list is detected, the registration tool may merge the line containing the matching portion with the lines before and after it and compare it again with the classification list, etc. If the control codes or tags indicating line breaks have not been removed in advance as described above, they may be removed when merging the multiple lines to be deleted.

If the same string is detected multiple times, the string may be output as a candidate only once. If separate strings that contain a detected string are detected, only one of them may be output as a candidate. If one of them is included in the registration list, the registered string may be output preferentially regardless of its length. If none of the detected strings are included in the registration list, it may be preset as to whether the longer or shorter string will be output preferentially.

FIG. 4 is a diagram showing an example of the beginning portion of an electronic bookkeeping document.
As described above, from the description "invoice" including a space, "invoice" is detected as a candidate document type. In addition, "To AAA Co., Ltd." and "BBB Co., Ltd." are detected as business partner types. Of these, "To" can be deleted as the above-mentioned excluded word. If either AAA Co., Ltd. or BBB Co., Ltd. is the company, the company name is excluded according to the exclusion list, and the other is made a candidate for classification. Conversely, if either one is already registered in the classification list, the registered corporate name is made a higher-ranked classification candidate. If there are multiple classification candidates, the multiple classification candidates may be displayed in parallel by the display unit 14, and any of them may be selected by the user. If there is only one classification candidate, the user can simply approve the candidate.

In the database, a classification type can be defined for each of multiple keys. As described above, selection and registration operations are possible for both document types and business partner types. The display and input operations for selection may be performed in parallel for multiple keys, or may be performed one by one in sequence.

Figure 5 is a flowchart showing the control procedure by the CPU 11 of the monitoring control process executed by the monitoring tool in the information processing device 1 of this embodiment. This monitoring control process can be started automatically when the information processing device 1 is started, or can be started at any timing by a user's input operation, etc. Once started, the monitoring control process is repeatedly and continuously executed until an end command is issued by a separate interrupt process, etc.

The CPU 11 acquires a file list of a folder to be monitored (S1). As described above, the folder to be monitored may be a "download folder." The CPU 11 compares the file list with the file list acquired in the previous process S1 (S2).

The CPU 11 determines whether or not any files have been added to the previous file list as a result of the monitoring (S3). The CPU 11 may detect not only added files, but also updated files with the same name. If it is determined that no added files have been added (S3; NO), the CPU 11 returns to process S1.

If it is determined that there is an additional file (S3; YES), the CPU 11 determines whether the additional file is in PDF format (S4). If it is determined that the additional file is not in PDF format (S4; NO), the processing of the CPU 11 returns to processing S1. If it is determined that the additional file is in PDF format (S4; YES), the CPU 11 calls and executes document classification control processing by the registration tool (S5). Then, the processing of the CPU 11 returns to processing S1.

A predetermined waiting time may be set before returning to process S1. Alternatively, the CPU 11 may wait without executing process S1 until an operation on the target folder is detected.

Figure 6 is a flowchart showing the control procedure by the CPU 11 of the document classification control process executed by the registration tool in the information processing device 1.

The CPU 11 acquires the document data of the target folder (S51). The CPU 11 extracts the entire text data from the document data. The CPU 11 identifies the line break positions in the entire text data, and obtains line data by extracting one line at a time from the top (S52). The CPU 11 deletes spaces (including indents, tabs, tag designations, etc.) from each extracted line of data to generate the target character string (S53).

The CPU 11 refers to the classification definition data 135 and searches for keywords contained in each line of text data (S54). As described above, the CPU 11 may limit the lines to be searched for keywords to a predetermined first line. Alternatively, the CPU 11 may select the lines to be searched for keywords based on the character size of each line (e.g., the line with the largest character size). The CPU 11 sets a classification destination candidate corresponding to the keyword (S55). The classification destination candidate may be, for example, simply a line of text containing the keyword with the excluded word deleted. Furthermore, if a classification different from the keyword is set in the classification definition data 135, the set classification name is set as the classification destination candidate.

The CPU 11 causes the display unit 14 to display a list of the set classification destination candidates (S56). When displaying the list, if there are multiple classification destination candidates, the CPU 11 may lower the display priority by displaying classification destination candidates that include an excluded item included in the exclusion list, such as the company's name, below classification destination candidates that do not include an excluded item included in the exclusion list. The CPU 11 waits for an input operation to the operation reception unit 15 and receives a classification selection operation. The CPU 11 confirms the classification in response to the selection operation (S57). Note that if an appropriate classification is not included in the displayed candidates or if the candidate name is inaccurate, the user can directly input the name of an appropriate classification through the operation reception unit 15. The CPU 11 sets the input name as a new classification and adds it to the classification list.

The CPU 11 determines whether the document data is a file to be classified and registered in a database, i.e., electronic ledger data (S58). If it is determined that the file is not a file to be classified and registered (S58; NO), the CPU 11 ends the document classification control process and returns the process to the monitoring control process.

If the document data is determined to be a file to be classified and registered (S58; YES), the CPU 11 adds classification information to the document data (S59). The CPU 11 registers the document data in a database (S60). The CPU 11 deletes the registered document file data from the target folder (download folder) (S61). The CPU 11 ends the document classification control process and returns the process to the monitoring control process.
At least steps S52, S54, and S55 of this document classification control process constitute the information processing method of this embodiment, and form processing means in the program 132 of this embodiment.

As described above, the information processing device 1 of this embodiment includes the CPU 11. The CPU 11 performs a process of generating a target character string based on lines extracted from an electronic document, comparing the generated target character string with a predetermined character string (keyword), and outputting a candidate classification destination for the electronic document based on the result of the comparison. If the extracted line contains a space, the CPU 11 deletes the space from the line to generate the target character string.
In this way, when there are multiple, especially a large number, electronic documents of the same type, the information processing device 1 can easily identify and show the user possible classification destinations. In particular, document titles used for classification often contain blank spaces such as spaces and tabs. By excluding these spaces when searching for character strings, the information processing device 1 can easily reduce missed detections and detect and output possible classification destinations. This allows the user to easily classify and manage electronic documents, and to more easily call up the electronic documents in the future.

Furthermore, the CPU 11 may perform the above process for a predetermined number of lines starting from the top line of the electronic document.
Document names that indicate document types that can be used for classification types, destinations that indicate business partner types, or document creators are often written near the beginning of a document. Therefore, the information processing device 1 simplifies processing by limiting the number of lines to be processed to a specific number of lines from the beginning. In addition, unnecessary search results are not obtained from other lines, so unnecessary classification candidates are not increased, making it easier for the user to select.

The CPU 11 may also lower the output priority of a target string when the target string contains an object to be excluded. There are strings, such as a company's name, that are not objects to be classified but are likely to be detected as possible classification destinations. By registering such strings as objects to be excluded in an exclusion list in advance, the information processing device 1 can make it difficult to select unnecessary classification destination candidates.

In addition, when an electronic document is stored in a predetermined location (such as a folder), the CPU 11 performs processing on the electronic document. That is, the information processing device 1 automatically starts processing related to classification and registration in a database for electronic documents added to a specific folder such as a download folder. Therefore, the user does not need to start the registration process each time, reducing the user's processing effort.

The specific folder may also be a default location where documents attached to e-mails are stored. This allows the information processing device 1 to easily classify and register in the database electronic documents sent as e-mail attachments. This further reduces the user's workload.

The electronic document may also be a document related to an electronic ledger. In recent years, accounting processing has shifted to electronic processing, and processing related to electronic ledger is increasing. As a result, a large number of fixed electronic documents such as purchase orders, quotations, and invoices are exchanged electronically. The information processing device 1 greatly reduces the effort required to classify and manage such electronic documents.

The CPU 11 may first extract the entire text content from the electronic document, and then determine each line based on the specified line break position within the entire text. Depending on the document data, the line break position may be difficult to determine by sequentially extracting the text, so by identifying the line break position from the entire text data, it is possible to more reliably avoid erroneous determination of the line break position.

When extracting text data line by line to generate a target character string, the CPU 11 may extract the line containing the character with the largest character size. When performing a structural analysis of a document as described above, the character size of each piece of text can be identified. Document names and the like are often written in the largest font size as titles. Therefore, the information processing device 1 can easily obtain appropriate classification candidates by selectively extracting such lines to generate a target character string.

The information processing device 1 also includes a display unit 14 and an operation reception unit 15. The CPU 11 displays classification destination candidates on the display unit 14. The CPU 11 classifies the electronic document into a classification destination according to an input operation received by the operation reception unit 15.
Therefore, the user can easily determine an appropriate classification destination.

In addition, the information processing method of this embodiment performs a process of generating a target string based on lines extracted from an electronic document, comparing the generated target string with a predetermined string (keyword), and outputting a candidate classification destination for the electronic document based on the result of the comparison. In this process, if the extracted line contains a space, the space is deleted from the line to generate the target string.
According to this information processing method, when there are multiple, particularly many, electronic documents of the same type, the CPU 11 can delete unnecessary spaces from the electronic documents, appropriately set the search target character string, and automatically and easily identify and show the classification candidates to the user. Therefore, the user can easily classify and manage the electronic documents, and can later more easily call up the electronic documents.

In addition, by installing the program 132 of this embodiment on a computer and making it executable, the user can easily and more accurately sort and manage many similar electronic documents. This greatly reduces the user's workload.

The present invention is not limited to the above-described embodiment, but may be modified in various ways.
For example, in the above embodiment, multiple character strings included in the same classification are registered separated by commas, but this is not limited to this. For example, they may be separated by spaces or tabs. Alternatively, all character strings to be detected may be registered separately. In this case, if a character string and a classification are different, the character string and the classification may be stored in association with each other.

In addition, in the above embodiment, the document type and the customer type are considered as classification items (keys) of electronic documents, but the classification items are not limited to these. For example, the transaction date and time, transaction amount, product (service), etc. may be used as classification items.

In the above, the character strings to be detected are expressed using regular expressions, but regular expressions do not have to be used. All patterns to be detected may be covered. As described above, the regular expressions may be selectable from among "company", "corporation", "office", and English expressions depending on the bias of business partners. Alternatively, character strings based on all regular expressions may be searched for from the beginning. However, if there are a large number of candidates to select from, the effort of selecting from the candidates may be greater than the effort of directly entering the candidates. Therefore, it is preferable to select regular expressions so that too many unnecessary candidates are not selected.

In addition, although the above description has been given using examples of email attachments and data downloaded via a network, the present invention is not limited to these. For example, electronic document files may be acquired from portable recording media such as USB memory. Furthermore, in addition to or instead of documents acquired from outside, electronic document files that are created by the user and sent to outside parties may also be subject to classification.

In the above, electronic document data related to electronic ledgers is the target of classification, but this is not limited to this. Any document that is typical and can be classified based on the content of the text contained in the document may be the target of classification. In addition, the electronic document has been described as being in PDF format, but the electronic document is not limited to this. The target of classification may be any other format of electronic document as long as it is in a format used as a typical transaction document, etc. In addition, the process of extracting each line of text from an electronic document is not limited to extracting the entire text and then dividing it into sentences. Line breaks may be detected sequentially and the text of each line may be extracted one by one.

In the above, the information processing device 1 such as a PC classifies and stores documents on its own, but this is not limited to the above. The information processing device 1 may request an operation related to classification from another device and obtain only the classification results. Alternatively, the information processing device 1 may transmit electronic document data including classification information to an external database server or the like, and have the electronic document data stored by the database server. The database device may also be an external auxiliary storage device, a storage device on a network, or a cloud server.

In the above description, the storage unit 13 is exemplified by a non-volatile memory such as a HDD or flash memory as a computer-readable medium for storing the program 132 related to the document classification control of the present invention, but is not limited to these. As other computer-readable media, other non-volatile memories such as MRAM and portable recording media such as CD-ROMs and DVD disks can be applied. Furthermore, a carrier wave can be applied to the present invention as a medium for providing data of the program related to the present invention via a communication line.
In addition, the specific configurations, contents and procedures of the processing operations, etc. shown in the above embodiments can be modified as appropriate without departing from the spirit of the present invention. The scope of the present invention includes the scope of the invention described in the claims and its equivalents.

1 Information processing device 11 CPU
12 RAM
13 Storage unit 131 Email software 132 Program 133 Download data 134 Document database 135 Classification definition data 14 Display unit 15 Operation reception unit 16 Communication unit

Claims (11)

a processing unit that performs a process of generating a target character string based on a line extracted from an electronic document, comparing the generated target character string with a predetermined character string, and outputting a classification destination candidate for the electronic document based on a comparison result;
The processing unit is an information processing device in which, if the extracted line contains spaces, the processing unit deletes the spaces from the line to generate the target character string. The information processing device according to claim 1, wherein the processing unit performs the processing for a predetermined number of lines starting from the first line of the electronic document. The information processing device according to claim 1, wherein the processing unit lowers the priority of the output of the target string when the target to be excluded is included in the target string. The information processing device according to claim 1, wherein the processing unit performs the processing on the electronic document when the electronic document is stored in a predetermined location. The information processing device according to claim 4, wherein the location is a preset location where a document attached to an e-mail is stored. The information processing device according to claim 1, wherein the electronic document is a document related to an electronic ledger. The information processing device according to claim 1, wherein the processing unit extracts an entire text from the electronic document and determines each of the lines based on a specified position of a line break in the entire text. The information processing device according to claim 1, wherein the processing unit extracts a line containing a character with a maximum character size when generating the target character string. A display unit and an operation receiving unit are provided,
The processing unit includes:
displaying the classification destination candidates on the display unit;
The information processing apparatus according to claim 1 , wherein the electronic document is sorted into a sorting destination according to an input operation accepted by the operation acceptance unit. 1. An information processing method for performing a process of generating a target character string based on lines extracted from an electronic document, comparing the generated target character string with a predetermined character string, and outputting a candidate classification destination for the electronic document based on a comparison result, comprising:
and if the extracted line contains spaces, deleting the spaces from the line to generate the target character string. On the computer,
generating a target character string based on the lines extracted from the electronic document, comparing the generated target character string with a predetermined character string, and selecting a classification destination candidate for the electronic document based on the result of the comparison;
In the process, if the extracted line contains spaces, the program deletes the spaces from the line to generate the target character string.

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