JP2011076627A - Interaction management device, method, program, and consciousness extraction system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To extract the original consciousness of a user by smoothly developing interaction between a user and a system and giving sense of security and sense of reliability to the user during the interaction. <P>SOLUTION: An interaction management device includes: an interaction scenario database; a scenario selection means for selecting an interaction scenario about requested information from the interaction scenario database; a response generating means for preparing a response sentence about the requested information on the basis of the selected interaction scenario and giving the response sentence to a user terminal; an action decision means for receiving an attribute and an attribute value to the attribute as response sentence analysis results from a response sentence analyzing means for analysis of a user response sentence to the response sentence, retrieving one or more interaction scenarios corresponding to a response condition from a data base, and determining the next action according to each interaction scenario; and an interaction control means for performing interaction control with the user according to the determined next action. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a dialog management apparatus, method, program, and consciousness extraction system. For example, in an information retrieval system, a dialog management apparatus, method, program, and consciousness that extract user consciousness from a dialog between the user and the system. It can be applied to an extraction system.

  Information analysis technology and information retrieval technology to find necessary information from a large amount of diverse information existing on the network as the information society progresses are not limited to the information industry, but communication, media, advertising, content, distribution, etc. This has become an important issue directly linked to strengthening the competitiveness of all industries that utilize information.

  Various systems such as Google (registered trademark) and Yahoo (registered trademark) have been put to practical use as information analysis / information retrieval systems for retrieving information existing on the network.

  In these information analysis / information search systems, it is common to introduce information with a large number of hits of input keywords in order from the top. Therefore, in order to search for desired information, the user needs to input information keywords correctly, but may not know what keywords should be input.

  Therefore, as a technology for solving such problems, for example, an automatic keyword expansion technology that displays keywords used together with input keywords, a recommendation system that introduces products from word-of-mouth information by many users, and the like are adopted. Is also possible.

  However, the technique as described above introduces representative information recommended by a larger number of users, and does not necessarily introduce specific individualized information of each user.

  Therefore, by exchanging dialogue with the user and repeating the questions that are gradually delved into the dialogue, the user's really desired needs and values are extracted and information that the user is aware of is retrieved. Information analysis and information retrieval technologies that can be used are proposed.

  As described above, in a system that analyzes the user's consciousness and searches for information according to that consciousness, the user's conscious information that matches the attribute information of the system is correctly extracted from the dialogue with the user. Is required.

  Patent Document 1 describes a technique related to a conventional interactive information search system. Patent Document 1 describes a technique for optimizing the number of dialogues because the number of cases to be narrowed down, the time required for narrowing down, and the number of erroneous recognitions increase as the number of dialogues increases.

JP 2000-276487 A

  However, since the information analysis / information search technology currently proposed aims to search for information that the user is conscious of, as described above, it is necessary to find out that the user is originally conscious.

  In this case, it is not possible to search for the original user consciousness by simply asking the user for information necessary for information retrieval. For example, when a person talks to the person, a trust relationship is established with a person who has a conversation with the person. In addition, when developing a conversation, when it comes to another topic, it may reveal the awareness of the previous topic for the first time.

  In order to perform such actions in the above-mentioned system, in the dialogue with the user, how to proceed with the dialogue, what topics to take up, how to trust with the user, The question is whether to create a sense of security.

  Therefore, the present invention provides a sense of security and reliability to the user and extracts the user's original consciousness while smoothly developing the dialogue between the user and the system and developing the dialogue. It is an object of the present invention to provide a dialogue management apparatus, method and program, and a consciousness extraction system capable of performing the above.

  In order to solve such a problem, the dialogue management apparatus according to the first aspect of the present invention includes: (1) a dialogue scenario in which an attribute of information and a response action corresponding to the attribute of information are set; A dialogue scenario database for storing a plurality of dialogue scenarios in which response actions corresponding to attribute values corresponding to the attributes are set; and (2) a dialogue scenario database for the dialogue scenarios of the attributes based on information attributes requested from the information requesting means. (3) When a response sentence is described in the response action corresponding to the attribute of the dialogue scenario selected by the scenario selection means, a response is generated and given to the user terminal And (4) an attribute obtained by analyzing the answer sentence analyzing means based on the user answer sentence answered by the user to the response sentence. One or more interaction scenarios that match the user's attribute value for the attribute are received from the interaction scenario database, and the attribute value for the attribute that is set in any interaction scenario is received. Action determining means for determining the response action as the next action, and (5) dialog control means for performing dialog control according to the next action determined by the action determining means, (6) the dialog control means is (6 -1) When a preset response sentence to be given to the user terminal is described in the response action related to the next action, the response generation unit generates the response sentence and gives the response sentence to the user terminal (6-2) If the response action related to the next action describes the attribute of another dialogue scenario to be called next, the scenario selection means And selects requesting the other interactive scenario attribute described in the response action.

  The dialogue management method of the second aspect of the present invention includes a dialogue scenario in which an attribute of information and a response action according to the information attribute are set, and a response action according to the attribute value of the information attribute and the attribute of information. A dialogue scenario database for storing a plurality of set dialogue scenarios, a scenario selection unit, a response generation unit, an action determination unit, and a dialogue control unit. (1) The scenario selection unit is requested from the information request unit. A scenario selection step of selecting a dialogue scenario of the attribute from the dialogue scenario database based on the attribute of the information, and (2) the response generation means in response action according to the attribute of the dialogue scenario selected by the scenario selection means, When a response sentence is described, a response generation step for generating the response sentence and giving the response to the user terminal, and (3) an action determining unit, One or a plurality of attribute values that the user is aware of for the attribute obtained by analyzing the answer sentence analysis means based on the user answer sentence answered by the user with respect to the answer sentence, and match the attribute value of the user for the attribute An action determination step of searching for a dialog scenario from the dialog scenario database and determining a response action corresponding to the attribute value for the attribute set in one of the dialog scenarios as the next action, and (4) dialog control means, A dialog control step of performing dialog control according to the next action determined by the action determination means, and (5) the dialog control means gives (5-1) a response action related to the next action to the user terminal in advance. When the set response text is described, the response generation means generates the response text, requests that the response text be given to the user terminal, (5- ) When an attribute of another dialogue scenario to be called next is described in the response action related to the next action, the scenario selection means requests to select the other dialogue scenario having the attribute described in the response action. It is characterized by doing.

  The dialogue management program of the third aspect of the present invention includes a dialogue scenario in which an attribute of information and a response action according to the information attribute are set, and a response action according to the attribute value of the information attribute and the attribute of information. A computer comprising a dialogue scenario database for storing a plurality of set dialogue scenarios; (1) scenario selection means for selecting a dialogue scenario of the attribute from the dialogue scenario database based on attributes of information requested by the information request means; (2) Response generation means for generating a response sentence and giving it to the user terminal when a response sentence is described in the response action corresponding to the attribute of the dialogue scenario selected by the scenario selection means; and (3) Response The user's response to the attribute obtained by analyzing the response sentence analysis means based on the user's answer sentence One or more interaction scenarios that match the attribute value of the user for the attribute are retrieved from the interaction scenario database, and a response action corresponding to the attribute value for the attribute that is set in one of the interaction scenarios Is determined as a next action, and (4) functions as a dialog control means for performing dialog control according to the next action determined by the action determination means. (5) The dialog control means (5) -1) When a preset response sentence to be given to the user terminal is described in the response action related to the next action, the response generation unit generates the response sentence and gives the response sentence to the user terminal (5-2) If the response action related to the next action describes the attribute of another dialogue scenario to be called next, the scenario And selects requesting the other interactive scenario attribute described in the selection means in the response action.

  The consciousness extraction system according to the fourth aspect of the present invention includes (1) a dialogue scenario in which an attribute of information and a response action corresponding to the attribute of information are set, and a response corresponding to the attribute value of the attribute of information and the attribute of information A dialogue management device that gives a response sentence to the user terminal according to a plurality of dialogue scenarios including a dialogue scenario in which an action is set, receives a user answer sentence for the response sentence from the user terminal, and interacts with the user; (2) An answer sentence analyzing apparatus that analyzes an attribute value perceived by a user based on a user answer sentence received from a user terminal, and (3) an dialogue that accumulates an attribute value of the user for an attribute for each dialogue scenario for each user. And an information storage device, wherein the dialogue management device corresponds to the dialogue management device according to the first aspect of the present invention.

  According to the present invention, it is possible to extract a user's original consciousness by providing a sense of security and trust to the user while smoothly developing a dialogue between the user and the system and developing the dialogue. Can do.

It is a block diagram which shows the internal structure of the dialogue control apparatus of 1st Embodiment (the 1). It is a block diagram which shows the whole structure of the laddering type search system of 1st Embodiment. It is a block diagram which shows the structure of the laddering dialog engine of 1st Embodiment. It is a block diagram which shows the internal structure of the dialogue control apparatus of 1st Embodiment (the 2). It is a block diagram which shows the structure of the dialogue scenario database of 1st Embodiment. It is a flowchart which shows the process of the dialogue control apparatus of 1st Embodiment. It is a flowchart which shows the action determination process of 1st Embodiment. It is a figure which shows the structural example of the dialogue sentence of 1st Embodiment. It is a block diagram which shows the structure of the scenario of 1st Embodiment. It is a block diagram which shows the structure of the scenario of 1st Embodiment. It is explanatory drawing explaining the schematic progress of the laddering dialog by the laddering dialog engine of 1st Embodiment. It is an example of the display screen displayed on the user terminal (browser) of 1st Embodiment.

(A) First Embodiment Hereinafter, a dialogue management apparatus, method and program, and a first embodiment of a consciousness extraction system according to the present invention will be described in detail with reference to the drawings.

  In the first embodiment, a dialogue management apparatus, method and program, and a consciousness extraction system according to the present invention are used, for example, a laddering type search service is adopted, and predetermined information is obtained from information conscious of a user and search target information. An example is shown in which an attribute and an attribute value are extracted and applied to an information analysis / information search system that searches for and introduces information that matches information perceived by the user.

(A-1) Configuration of First Embodiment (A-1-1) Description of Overall Configuration of Laddering Type Search System First, in the following, the dialog management device, method and program of the present invention, and consciousness extraction system are applied. An overall image of the laddering type search system will be described with reference to the drawings.

  FIG. 2 is an overall image diagram illustrating an overall image of the laddering search system 9 according to the first embodiment. FIG. 3 is a configuration diagram showing the configuration of the laddering dialog engine 1 that implements the laddering search system 9.

  In FIG. 2, a laddering search system 9 according to the first embodiment includes a laddering search service site 3 having a laddering dialog engine 1 that can be connected through a network, and a service site 2 (2-1) that provides various services. ˜2-n; n is a positive integer) and Web information 4 existing on the network.

  The user interface (UI) means 90 includes a Web server 901 that is accessible from a user terminal (browser) operated by the user U1 and provides a laddering search service. Further, the user interface (UI) means 90 has a speech synthesis / recognition unit 902 as necessary, and can realize a conversation by speech when the information from the user U1 is speech information. It is.

  The laddering dialogue engine 1 asks the user U1 questions and analyzes the user U1's answer to each question, thereby proceeding with the dialogue with the user U1 and analyzing the consciousness that the user U1 really wants. Is.

  Further, the laddering dialogue engine 1 acquires information provided by the service site 2 and Web information 4 as search target information, and extracts attributes and attribute values corresponding to the attributes from the information and Web information 4 of the service site 2. Then, information having an attribute value corresponding to the response information from the user U1 is searched, and information having an attribute value corresponding to the consciousness of the user U1 is introduced to the user U1.

  Here, laddering refers to a method of drawing out the needs and values of a partner by repeating questions that are gradually digged down in the dialogue with the partner.

  As a kind of dialogue with the user that the laddering dialogue engine 1 performs, for example, a question type in the “YES / NO” format in which the system makes the user answer YES or NO, or a question type in the “selection from choice” format In addition, a question type that allows the user to freely answer, a question type that prompts the user to speak spontaneously by agreeing or paraphrasing the user's answer, and the like can be applied.

  In FIG. 2, the laddering dialogue engine 1 includes a knowledge acquisition function unit 12 that acquires information for advancing the dialogue from the service site 2 and the Web information 4 and knowledge information for extracting the consciousness of the user U1 through the network. It has a term knowledge / domain knowledge DB 13 for storing knowledge information acquired by the acquisition function unit 12.

  The laddering dialogue engine 1 also has a domain-specific dialogue scenario DB 14 that stores a scenario for advancing the dialogue for each domain according to the types of service sites 2 that can be connected through the network.

  Further, the laddering dialogue engine 1 includes a laddering dialogue control function unit 11 that advances a dialogue with the user U1 while referring to the term knowledge / domain knowledge DB 13 and the domain-specific dialogue scenario DB 14.

  The laddering dialogue control function unit 11 asks “deep digging” for further deepening questions in order to clarify the user's consciousness, or “paraphrasing” for rephrasing the user utterances to another expression with a high degree of abstraction. (The above is usually handled by the scenario), “Confirmation” to confirm the user's answer, “Information provision” to provide various information to the user in order to increase the motivation of the user's remarks ( Processes such as “summary” that summarizes and reuses information heard in the past.

  Furthermore, the laddering dialogue engine 1 includes a search target analysis function unit 15 that analyzes search target data obtained from the search target data 21 of each service site 2, and a search target analysis result analyzed by the search target analysis function unit 15. Is stored in the search target analysis result DB 16.

  The matching function unit 17 extracts information matching the answer analysis result of the user U1 analyzed by the laddering dialogue control function unit 11 (information extracted from the user U1) from the search target analysis result DB 16, and the matching status is extracted. This is given to the laddering dialogue control function unit 11.

  The various service sites 2-1 to 2-n are service sites that provide various types of information to users through a network.

  Various service sites 2-1 to 2-n correspond to service domains of a wide variety of companies and organizations, for example, job introduction domains for residential workers, housing information introduction domains, various shopping site domains, and travel plans. / Domain sites provided by companies such as personal navigation domains, broadcast and movie content industry domains, community sites such as so-called blogs and SNS (social network sites), domain sites such as administrative agencies, and surveys -Domain sites provided by companies and organizations for counseling (for example, medical care, healthcare, welfare and questionnaire surveys).

  The Web information 4 is Web information existing on the network, and is information that the laddering dialog engine 1 can access through the network.

  Next, the internal configuration of the laddering dialog engine 1 will be described with reference to FIG.

  In FIG. 3, the laddering dialogue engine 1 includes a dialogue management means 10, a matching means 20, a matching target analysis means 30, a scenario management means 50, a dialogue result summarization means 60, a domain knowledge acquisition means 70, a user utterance analysis means 80, a user interface. (UI) It has at least the means 90.

  The dialogue management means 10 controls processing in the laddering dialogue engine 1. The dialogue management means 10 repeatedly asks various questions to the user U1 who desires to search, accumulates answers (dialog contents) from the users to those questions, and aggregates the accumulated dialogue logs. Information that the user is really aware of is extracted, information and contents that match the information that the user is aware of are retrieved and introduced to the user U1.

  The dialogue management means 10 has a dialogue control unit 101 for asking a question to the user U1 as a main functional unit, advancing the next dialogue based on an answer analysis result from the user U1, and executing dialogue control, a scenario relating to the dialogue The scenario selection means for asking a question to the user U1 or changing a scenario based on an answer from the user U1 and selecting a scenario that does not give a sense of incongruity about the dialogue with the user U1. Based on the scenario selected by the unit 103 and the scenario selection unit 103, at least a response generation unit 104 that generates a response sentence to the answer from the user U1 is provided.

  The matching unit 20 receives the response analysis result of the user U1 analyzed by the dialogue management unit 10 (information extracted from the user U1) from the dialogue management unit 10, and performs matching with the information acquired from the service site 2. .

  As a main functional unit, the matching unit 20 provides a response analysis result of the user U1 received from the dialogue control unit 101 to the matcher 202, and provides information matched by the matcher 202 to the domain knowledge acquisition unit 70. A search is performed from the service site 2 based on the matcher 202 that performs the matching process between the target data and the personal registration data, the matching process between the user U1 answer analysis result and the search information of the service site 2, and the user U1 answer analysis result. It has at least a setter 203 for determining an object.

  The matching target analyzing unit 30 converts matching target data (that is, information related to attributes for asking the user U1) and personal registration data into a predetermined data format, and uses the dialog result and domain knowledge to perform the matching. The target data and personal registration data are expanded.

  The matching target analysis unit 30 includes, as main functional units, a target data DB 303 that stores target data to be matched indicating attributes, a personal registration data DB 304 that stores personal registration data of the user U1, a target data DB 303, and a personal registration DB 304. A converter 301 that converts stored target data and personal registration data into a predetermined data format, and data converted into a predetermined data format by the converter 301 based on domain knowledge and log information of dialogue results, It has at least an enhancer 302 that converts it into data that is expanded into data or the like.

  The domain knowledge acquisition means 70 acquires domain information and knowledge information provided on the service site 2 from the service site 2 and other Web information 4 through the Web information 4.

  The domain knowledge acquisition means 70 acquires domain knowledge information (namely, terms) relating to the field to be searched through the Web, and gives the acquired domain knowledge information (hereinafter also simply referred to as domain knowledge) to the matching target analysis means 30. A domain knowledge editor 701 that converts the domain knowledge into a predetermined data format, and a domain knowledge DB 702 that stores the domain knowledge converted into a predetermined data format as a systematic collection (hereinafter also referred to as an ontology).

  The scenario management means 50 generates and manages a scenario for each domain while referring to the domain knowledge DB 702. The scenario management unit 50 generates a scenario for interacting with the user U1 while referring to the domain knowledge DB 702, changes the scenario according to the control of the action determining unit 102 of the dialogue management unit 10, and A scenario editor 501 for editing is provided. The scenario editor 501 can generate a dialogue scenario based on the expanded target data in cooperation with the enhancer 302 of the matching target analysis unit 30 for the conversation scenario with the user. Further, the dialogue scenario generated by the scenario editor 501 is selected by the scenario selection unit 103.

  The dialogue result summarizing means 60 reads the log information stored in the log DB 601 under the control of the dialogue control unit 101 by reading the log DB 601 that stores the logs exchanged in the dialogue between the system and the user U1, and the dialogue control unit 101. And a summarizer 603 that performs a summary process on the answer of the user U1 using the extended / target data and the extended / personal data.

  The user utterance analysis unit 80 inputs the answer of the user U1 through the dialogue control unit 101, and analyzes information that the user is aware of based on the input answer information of the user U1. Further, the user utterance analysis unit 80 provides the dialog control unit 101 with analysis information that the analyzed user is aware of.

  As shown in FIG. 3, the user utterance analysis unit 80 includes, as main functional units, a consciousness analysis unit 801, an expression normalization unit 802, a syntax analysis unit 803, a morpheme analysis unit 804, a dictionary converter 805, and a consciousness analysis dictionary 806. And at least a translation dictionary 807.

  The consciousness analysis dictionary 806 stores various information necessary for consciousness analysis. In FIG. 3, the consciousness analysis dictionary 806 is shown as a single dictionary for convenience of explanation, but is intended for consciousness analysis. For example, morpheme information, syntax information, normalization information Etc. are stored. The translation dictionary 807 stores translation information.

  The dictionary converter 805 translates information stored in the consciousness analysis dictionary 806 as necessary while referring to the translation dictionary 807 and the consciousness analysis dictionary 806.

  The morphological analysis unit 804 acquires the response information of the user U1 or the search target information such as the service site 2 from the dialogue control unit 101, and performs consciousness analysis on the search target information such as the response information of the user U1 or the service site 2. The morphological analysis is performed with reference to the dictionary 806.

  The syntax analysis unit 803 performs syntax analysis on the search target information such as the reply information of the user U1 or the service site 2 based on the morpheme analysis result by the morpheme analysis unit 804 while referring to the consciousness analysis dictionary 806. It is.

  The expression normalization unit 802 performs regular expression on the syntax analysis result by the syntax analysis unit 803 while referring to the consciousness analysis dictionary 806 and the domain knowledge DB 702.

  The consciousness analysis unit 801 extracts consciousness information perceived by the user included in the response information of the user U1 while referring to the consciousness analysis dictionary 805 and the domain knowledge DB 702. The user consciousness information extracted by the consciousness analysis unit 801 is stored in the personal registration data DB 304 of the matching target analysis unit 30 via the dialogue control unit 101.

(A-1-2) Dialog Management Device Next, the dialog management device according to the first embodiment will be described in detail with reference to the drawings. In the following, a case where the service site 2 is a job introduction domain site for a job changer will be described as an example.

  The dialogue management apparatus according to the first embodiment is realized as the dialogue management means 10 in the laddering dialogue engine 1 described above. In the following, the same sign “10” as that of the dialog management means is used for the dialog management apparatus.

  Of course, in the above-described laddering dialog engine 1, the dialog management means 10 introduces information according to the user's consciousness while interacting with the user by the laddering technique in cooperation with the various means 20 to 90 by software processing. Therefore, the place where information extraction processing described later is realized is not particularly limited.

  1 and 4 are configuration diagrams illustrating the configuration of the dialogue management apparatus 10 according to the first embodiment. FIG. 1 is a configuration diagram when the dialogue management apparatus 10 includes user personal information outside, and FIG. 4 is a configuration diagram when the dialog management apparatus 10 includes user personal information inside.

  As illustrated in FIGS. 1 and 4, the dialogue management apparatus 10 according to the first embodiment includes at least a dialogue control unit 101, an action determination unit 102, a scenario selection unit 103, and a response generation unit 104.

  The dialogue management apparatus 10 shown in FIG. 1 is linked at least with the Web server 901, the input sentence analysis module (user utterance analysis means) 80, the dialogue log (log DB) 601, and the matching means 20. Also, the dialogue management apparatus 10 shown in FIG. 4 cooperates at least with the Web server 901, the input sentence analysis module (user utterance analysis means) 80, and the dialogue log (log DB) 601.

  The dialogue control unit 101 controls functions realized by the dialogue management apparatus 10 and controls cooperation processing with external modules (for example, the Web server 901, the input sentence analysis module 80, the dialogue log 601, the matching unit 20, and the like). It is. The dialogue control unit 101 basically exchanges information between the action determination unit 102, the scenario selection unit 103, the response generation unit 104, and an external module.

  Specifically, the dialogue control unit 101 requests the scenario selection unit 103 to request the scenario by request information or answer statement determination, to generate a response statement to the response generation unit 104, and to analyze the input sentence to the input sentence analysis module 80 A request process, a response sentence determination request process for the action determination unit 102, and a dialog write request process for the dialog log 601 are performed.

  When the matching unit 20 receives a request for information that the matching unit 20 desires to acquire from the matching unit 20, the scenario selection unit 103 selects a scenario (hereinafter also referred to as an optimal scenario) for acquiring the information from the dialogue scenario 1031. It is.

  The scenario selection unit 103 gives the selected scenario to the dialogue control unit 101. At this time, the dialogue control unit 101 holds the scenario acquired from the scenario selection unit 103 as the current scenario 1011 and gives the scenario to the response generation unit 104.

  Here, the determination as to which attribute information is acquired from the user is made based on the matching result between the search target data and the user's answer data in the matching means 20, for example.

  As the dialogue scenario 1031, for example, a scenario for acquiring the information for all information requested by the matching unit 20 is set in advance. Further, as the dialogue scenario 1031, one corresponding to the dialogue scenario possessed by the scenario management means 50 shown in FIG. 3 can be applied.

  FIG. 5 is a configuration diagram showing a configuration of a dialogue scenario DB 502 that stores a plurality of dialogue scenarios 1031. As shown in FIG. 5, the dialogue scenario DB 502 includes a normal scenario group 51, a special scenario group 52, and a response sentence group 53.

  The normal scenario group 51 is a collection of scenarios for extracting requirements desired by the user in the dialog with the user U1. In this normal scenario group 51, scenarios for all attributes in the field related to the search target are set in advance.

  The special scenario group 52 responds to an irregular utterance from the user (for example, when the user asks a question about the utterance of the scenario) in the laddering dialogue with the user, or lubricates the dialogue with the user. A collection of scenarios to proceed. For example, “explanation scenario”, “confirmation scenario”, “neighboring scenario”, and the like are applicable. There is also a “default scenario” that is executed when an action for the user's utterance does not exist in the normal scenario.

  The response sentence group 53 is an example of a response sentence used in a normal scenario and a special scenario, and is also referred to as a response sentence seed. In the response sentence group 53, a response sentence that responds in advance is set, or a template having variables is set.

  The dialogue scenario DB 502 describes information scenarios based on information stored in the domain knowledge DB 702 shown in FIG.

  Further, the scenario in the dialogue scenario DB 502 can generate a response sentence using the contents of the expanded / personal data whose information is expanded by the enhancer 302 or the like. That is, you may make it hold | maintain the scenario replaced by the similar term.

  When the response generation unit 104 receives a scenario via the dialogue control unit 101, the response generation unit 104 generates a response sentence that responds to the user based on the response sentence seed of the scenario.

  Here, as a method of generating a response sentence by the response generation unit 104, for example, a method of creating a response sentence according to the response sentence group 53 with reference to the response sentence group 53 of FIG. At this time, when the response sentence is a template having a variable, the response sentence is completed by substituting the actual data obtained from the user into the variable.

  The response generation unit 104 gives the generated response sentence to the dialogue control unit 101. At this time, the dialogue control unit 101 gives the generated response sentence to the Web server 901 to be transmitted to the user U1.

  When the action determining unit 102 receives a user input sentence analysis result that is an answer from the user via the dialog control unit 101, the action determining unit 102 determines the next dialog action based on the input analysis result, and the determined next action Is given to the dialogue control unit 101. At this time, the dialogue control unit 101 controls to perform the next action according to the action determined by the action determination unit 102.

  Here, there are the following three actions as actions determined by the action determining unit 102. The first is to provide information to the matching means 20 and end the current scenario 1011. The second is to continue the current scenario 1011. Thirdly, a special laddering process is executed.

  This special processing of laddering means that it is difficult to continue a normal scenario due to an irregular utterance from the user (for example, when the user asks a question about the utterance of the scenario), or the current scenario (user required This is a process of selecting a scenario different from the current scenario and continuing the dialogue when a special response is required to facilitate the dialogue with the user.

(A-2) Operation of the First Embodiment Next, the process (dialog management method) of the dialog management apparatus of the first embodiment will be described with reference to the drawings. FIG. 6 is a flowchart illustrating processing of the dialogue management apparatus according to the first embodiment. The step numbers shown in FIGS. 1 and 6 are respectively corresponding numbers.

  First, when a request for information desired to be acquired from the matching means 20 is given to the dialogue control unit 101 (step S1), the dialogue control unit 101 makes a scenario request based on the request information to the scenario selection unit 103 (step S1). S2).

  At this time, the dialogue scenario 1031 stored in the dialogue scenario DB 502 is read into the scenario memory 1021 (step S111).

  For example, when the information requested by the matching unit 20 is “desired job category”, the scenario selection unit 103 selects a scenario for “desired job category” from the dialogue scenario 1031 and gives the scenario to the dialogue control unit 101 (step S1). S3).

  When the scenario selected by the scenario selection unit 103 is given to the dialogue control unit 101, the dialogue control unit 101 holds the scenario as the current scenario 1011 and gives a response statement seed of the current scenario to the response generation unit 104. A response sentence generation request is made (step S4).

  The response generation unit 104 generates a response sentence based on the response sentence seed in the scenario of the request information, and gives the created response sentence to the dialogue control unit 101 (step S5).

  For example, at this time, as a response sentence for “desired occupation”, the response generation unit 104 generates a response sentence “Do you have a job title?” Based on the response sentence seed.

  Then, the dialogue control unit 101 gives the response sentence generated by the response generation unit 104 to the Web server 901 (step S6), and asks a question to the user terminal (not shown) of the user U1.

  Thereafter, when an answer sentence to the question is given from the user U1 to the dialogue control unit 101 via the Web server 901 (step S7), the dialogue control unit 101 analyzes the answer sentence from the user U1 and the current scenario. It gives to the module 80 and the analysis request | requirement of the reply sentence is performed (step S8).

  In the input sentence analysis module 80, the input answer sentence of the user U1 is analyzed, and the analysis result is given to the dialogue control unit 101 (step S9).

  The input sentence analysis method in the input sentence analysis module 80 is not a feature of the present invention, and therefore detailed description thereof is omitted. For example, domain knowledge (ontology) in which information knowledge is systematically classified is used. Done. For example, when the answer sentence to the response sentence of the user U1 is “Nothing in particular”, the input sentence analysis module 80 gives the analysis result “No” to the dialog control unit 101.

  Upon receiving the answer sentence analysis result from the input sentence analysis module 80, the dialogue control unit 101 gives the answer sentence analysis result and the current scenario to the action determination unit 102 to request an answer sentence determination (step S10).

  Then, the action determination unit 102 determines the next action based on the answer sentence analysis result and the current scenario, and gives the determined action to the dialogue control unit 101 (step S11). That is, the action determination unit 102 determines whether to provide information to the matching means 20 to end the current scenario, to continue the scenario, or to perform special laddering processing.

  Here, the action determination process by the action determination unit 102 will be described in detail with reference to the drawings.

  FIG. 7 is a flowchart showing the action determining process by the action determining unit 102. FIG. 8 illustrates the contents of the laddering dialogue between the user U1 and the system.

  As shown in FIG. 8, the dialogue management apparatus 10 asks the user a response sentence “Why did you want to change your job?” In order to draw out the “reason for changing job” to the user, and the answer is as follows. Suppose you get a reply that the company went bankrupt. Then, it is assumed that “reason for job change (attribute name): bankruptcy (attribute value)” is given to the action determination unit 102 as an answer analysis result from the input sentence analysis module 80.

  In FIG. 7, the dialogue scenario 1031 of the dialogue scenario DB 502 shown in FIG. 5 is loaded on the scenario memory 1021 when the system is activated.

  When the answer analysis result is given to the action determination unit 102, the action determination unit 102 searches for a special scenario from the scenario memory 1021 based on the received answer analysis result (step S301).

  As described above, the behavior determining unit 102 searches for a special scenario before searching for a normal scenario, thereby selecting a special scenario that gives the user a sense of trust and security (“close scenario”), or It is possible to select a special scenario (“explanation scenario”) corresponding to a case where a user suddenly asks an unrelated question.

  If there is a special scenario that matches the answer analysis result (step S302), the matched special scenario is selected, and the action determination unit 102 gives the special scenario to the dialog control unit 101. Thereby, the response sentence action of the matched special scenario is executed under the control of the dialogue control unit 101 (step S303).

  Here, scenario progress processing by the action determination unit 102 will be described in detail.

FIG. 9 is an example of a special scenario. FIG. 9A shows an example of a close-up scenario, and FIG. 9B shows an example of a confirmation scenario.

  As shown in FIG. 9, each scenario has a “scenario key”, “priority”, “response sentence condition”, and “response sentence action”.

  Here, in FIG. 9, one or more sets of “response sentence condition” and “response sentence action” are defined in one scenario. The “response sentence condition” and the “response sentence action” are associated with each other, and when a certain “response sentence condition” is met, a response sentence action corresponding to the response sentence condition is executed.

  The “scenario key” is scenario identification information.

  “Response sentence action” defines an action when the “response sentence condition” is met. In FIG. 9, as an example of an action, a case where it is defined to respond with one preset response sentence is shown. However, the present invention is not limited to this, and it is possible to define responses of multiple response sentences, to define response sentences consisting of templates with variables using user personal data acquired from the user in the past, and to select options for the user A response statement with options to be defined, response statement continuation information that defines whether to continue or end the response, and if this ends, information on another scenario to be called next is defined Or changing the priority of scenarios or changing the importance of matching.

  “Response sentence condition” is a condition for executing a response sentence action. FIG. 9 illustrates a case according to a user attribute value. However, the present invention is not limited to this, and whether or not the attribute value is user personal data or expanded information acquired in the past, not on the condition that it was called from another scenario or acquired from the user this time It may be a condition.

  The “priority” of the normal scenario determines the priority of the attribute name scenario to be executed when a request is made for a plurality of information attribute names requested by the matching means 20 or when the matching means 20 does not exist. It is.

For example, the priority of the (A) job change reason scenario in FIG. 10 is 10, and (B) the priority of the desired job type scenario is 8. In this case, if there is no information request from the matching means, the job change reason scenario is executed before the desired job type scenario. In this way, the order in which questions are asked to the user can also be defined in the scenario (and the priority is rewritten in the response sentence action as in the example of (B) -1). You can also.)
On the other hand, the “priority” of the special scenario determines which special scenario is uttered in the special scenario (the definition of “priority” differs between the normal scenario and the special scenario).
For example, in the case of (A) and (B) in FIG. 9, a close-in scenario and then a confirmation scenario are generated as a system utterance ("That's sorry. So you want to change jobs." Scenario utterance).

  For example, when an answer sentence analysis result “reason for job change (attribute name): company bankruptcy (attribute value)” is given to the action determination unit 102, the action determination unit 102 sets the attribute name “reason for job change” and the attribute value “company bankruptcy” Search for a special scenario that uses as a response sentence condition. Here, it is assumed that two special scenarios (a close-up scenario and a confirmation scenario) illustrated in FIGS. 9A and 9B are searched (S41 in FIG. 7). Then, the action determination unit 102 notifies the dialog control unit 101 of two special scenarios.

  Upon receiving the special scenario, the dialogue control unit 101 gives a response sentence seed of the special scenario to the response generation unit 104 in accordance with the priority order based on the priority of the special scenario (step S13 in FIGS. 1 and 6).

  The response generation unit 104 generates a response text based on the response text seed from the dialog control unit 101, and gives the response text to the dialog control unit 101 (step S14 in FIG. 1). Then, a response sentence “I feel sorry” is given to the user U1 by executing the snuggle scenario, and a response sentence “I want to change my job” is given to the user U1 by executing the confirmation scenario (S42).

  On the other hand, in step S302, when there is no special scenario that matches the answer analysis result, or after executing the response sentence action of the special scenario, the behavior determination unit 102 matches the attribute name X (in this example, the reason for job change). Whether there is a scenario is searched (step S304).

  If there is a normal scenario that matches the answer analysis result (step S305), the matched normal scenario is selected, and the action determination unit 102 gives the normal scenario to the dialog control unit 101. Thereby, the response sentence action of the matched normal scenario is executed under the control of the dialogue control unit 101 (step S306).

  Here, the scenario progress process of the normal scenario will be described. FIG. 10 is an example of a normal scenario. Each scenario has a “scenario key”, “priority”, “response sentence condition”, and “response sentence action”. Furthermore, this illustrates a scenario configuration when jumping from scenario (A) to another scenario (B).

  For example, the behavior determining unit 102 searches for a normal scenario having the attribute name “reason for job change” and the attribute value “company bankruptcy” as a response sentence condition. Here, it is assumed that the normal scenario illustrated in FIG. Then, the action determination unit 102 notifies the dialogue control unit 101 that the response sentence action of the normal scenario shown in FIG. 10A is “jump to desired job type scenario”.

  Then, the dialogue control unit 101 requests the “desired job category” scenario from the scenario selection unit 103 (step S15 in FIG. 1). When the scenario selection unit 103 gives the “desired job category” scenario to the dialogue control unit 101, the scenario selection unit 103 holds the “desired job category” scenario as the current scenario and generates a response sentence seed of the newly jumped scenario as a response. A response sentence “What kind of work were you doing before?” Is given to the user U1 by executing the deep drill scenario (S43).

  As shown in FIG. 10 (A), “deepening” can be realized by jumping to another scenario in which the attribute value obtained from the user's utterance is further deepened.

  On the other hand, if there is no normal scenario with the attribute name “X (reason for job change)” that matches the answer analysis result in step S305, the behavior determination unit 102 determines that there is a normal scenario that matches the response sentence condition for all attribute names. It is searched whether it exists (step S307).

  If there is a normal scenario that matches the answer analysis result (step S 308), the matched normal scenario is selected, and the action determination unit 102 gives the normal scenario to the dialog control unit 101. As a result, a transition process from the normal scenario with the attribute name “X (reason for job change)” to another normal scenario with the attribute name “Y” is performed under the control of the dialogue control unit 101 (step S309).

  On the other hand, in step S308, if there is no normal scenario that matches the answer analysis result, or after the response sentence action of the normal scenario action in step S306 is executed, the action determination unit 102 is set as a default. A special scenario is given to the dialogue control unit 101 (step S310).

  In this case, based on the default special scenario determined by the action determination unit 102, the dialogue control unit 101 cooperates with the scenario selection unit 103 and the response generation unit 104, for example, “I ’m sorry, but I choose from the following options. A response sentence “Can you please do it?” Is transmitted to the user U1 (S45).

  As a result, when there is no scenario to be applied at all, a special scenario is set as a default so that some kind of response can be given or another question can be transferred.

  When the action determination unit 102 meets the response sentence condition of the scenario indicating the end, the action determination unit 102 gives a message to that effect to the dialog control unit 101 and writes the response sentence and the answer sentence about the scenario in the dialog log 601. The scenario is finished (step S12). The dialogue log 601 is written every time one scenario ends. Therefore, even when jumping from one scenario to another scenario, the response sentence and answer sentence of the previous scenario are written.

  In the above, the case where the personal information data is outside the dialogue management apparatus 10 as shown in FIG. 1 is exemplified, but the same operation is performed when the personal information data is inside the dialogue management apparatus 10 as shown in FIG. become.

  However, as shown in FIG. 4, when the personal information data is in the dialogue management apparatus 10, information requested to the dialogue control unit 101 (that is, data for extracting attribute values) is given priority. Assume that a request is made to the dialog control unit 101 in accordance with the priority order.

  FIG. 11 is an explanatory diagram for explaining the schematic progress of the laddering dialogue by the laddering dialogue engine 1.

  As shown in FIG. 11, in the dialogue between the user and the system, the first question Q1 (for personality), question Q2 (for career), ..., question Qn (n is a positive integer) (for the future) By expanding the contents, personal data other than the answer to the main question can also be acquired (S51, S52), and by extracting the user U1's consciousness information, each attribute is added to the extended personal data 304 of the user U1. The attribute values are filled (S53). Thereby, it is possible to perform matching between the attribute value of the individual and the attribute value obtained by the recruiter, and to output job data with a high degree of matching (S54). Further, the resumer 603 creates a resume from the expanded personal data by the summarizer 603 (S55).

  FIG. 12 is an example of a display screen displayed on the user terminal (browser) of the user U1. As shown in FIG. 12, on the display screen, the question display unit 91 displays the current question given from the laddering dialog engine 1, and the answer display unit 92 displays the contents answered by the user U1. The dialogue log display section 93 displays the contents of the dialogue exchanged so far. Further, the working condition display unit 94 displays conditions detected by the dialog engine 1 in the laddering dialog, that is, conditions input by the user U1. In the job list display unit 95, job search destinations searched by the laddering dialogue engine 1 are displayed.

  Note that the display screen shown in FIG. 12 is an example, and the following display is possible in addition to the display screen shown in FIG.

  (A) If you do not like the displayed company name, display to cancel the dialog log retroactively. For example, when a mark is clicked and clicked, the dialogue after the mark is canceled and the dialogue can be resumed from the mark.

  (B) When the displayed company name is clicked, the user data that has become a job offer condition for the company is highlighted. For example, when the job offer condition of the company is “Job Type: SE” and the user data is “Job Type: SE”, the desired job type of the user data is highlighted. In other words, it is easy to understand the recruitment conditions of each company.

  (C) There is another “Release Conditions” button, and the user looks at the currently displayed company list and presses this button if the conditions are too narrow. When this button is pressed, the system asks questions that relax the condition.

  In the above description, examples of “deep drilling”, “confirmation”, and “closeness” have been described. However, “paraphrase”, “information provision”, and “summary” can be performed as follows.

  For example, when “paraphrase” is executed, if the domain knowledge has a structure of, for example, “career up (superior concept)” − “want to acquire qualification (subordinate concept)”, “want to acquire qualification” from the user's utterance When the attribute value is acquired, “paraphrase” can be realized by referring to the value of the superordinate concept and responding “I want to improve my career”.

  For example, when “information provision” is executed, the domain knowledge can describe the meaning of each value, such as “route sales: a company that visits a predetermined customer”. For example, when the user utters “What kind of work is route sales?”, The utterance analysis of “What kind of work is?” By passing the result, the scenario of the special scenario is executed and the meaning of the route sales described in the ontology is acquired, and the response “Route sales are sales that visit a specific customer” is sent. In this way, “information provision” can be realized.

  Furthermore, for example, when "summary" is executed, the user's utterance history is retained and summarization is possible. By quoting and presenting the results in the middle of the dialogue, the dialogue can proceed smoothly.

(A-3) Effects of the First Embodiment As described above, according to the first embodiment, the dialogue control unit, the action determination unit, the scenario selection unit, and the response generation unit are provided, and these configuration requirements are linked. By doing so, in the laddering dialogue between the user and the system, it is possible to develop a dialogue that searches for consciousness according to the user's answer.

(B) Other Embodiments (B-1) In the first embodiment, an example of a service introduction site for job changers is shown as an example of a service site, but the present invention is not limited to this and exists on the network. It can be widely applied to information.

  As information on the network, text data, image data, moving image data, sound data, and the like can be used as search target data.

(B-2) Functions of various components realized by the laddering dialogue engine and the dialogue management device described in the first embodiment are realized by software processing. For example, the hardware configuration includes, for example, a CPU, a ROM, a RAM, and the like. The functions of various components are such that the CPU stores a processing program stored in the ROM and data necessary for processing. This is realized by executing using.

(B-3) The dialogue management device described in the first embodiment is not limited to being physically mounted on the same device, and various components are mounted on distributed devices. It may be. That is, various components may be arranged in a distributed manner.

  DESCRIPTION OF SYMBOLS 10 ... Dialog management apparatus, 101 ... Dialog control part, 102 ... Action determination part, 103 ... Scenario selection part, 104 ... Response generation part, 1031 ... Dialog scenario, 1021 ... Scenario memory, 601 ... Dialog log.

Claims (9)

An interactive scenario in which a plurality of interactive scenarios in which an attribute of information and a response action according to the information attribute are set, and an interactive scenario in which a response action according to the attribute value for the information attribute and the information attribute is set are stored A database,
A scenario selection means for selecting a dialogue scenario of the attribute from the dialogue scenario database based on the attribute of the information requested from the information requesting means;
A response generating means for generating a response sentence and giving it to the user terminal when a response sentence is described in the response action corresponding to the attribute of the dialogue scenario selected by the scenario selecting means;
One or a plurality of attribute values that the user is aware of for the attribute obtained by analyzing the answer sentence based on the user answer sentence answered by the user with respect to the response sentence, and match the attribute value of the user for the attribute Searching for the above-mentioned dialog scenario from the above-mentioned dialog scenario database, and determining a response action corresponding to the attribute value for the attribute set in any of the dialog scenarios as the next action,
Dialog control means for performing dialog control according to the next action determined by the action determination means,
The dialogue control means is
When a preset response sentence to be given to the user terminal is described in the response action related to the next action, the response generation means generates the response sentence and gives the response sentence to the user terminal. Request,
If the response action related to the next action describes the attribute of another interaction scenario to be called next, the scenario selection means requests the other interaction scenario with the attribute described in the response action to be selected. A dialogue management device characterized by: Each of the above dialogue scenarios
Regarding the attribute, at least a response action corresponding to the attribute for extracting the attribute value from the user and a response action corresponding to the attribute value corresponding to the attribute for advancing the dialogue using the attribute value extracted from the user A normal scenario including one,
2. A special scenario including a response action corresponding to an irregular utterance from the user in a dialog with the user and a response action that smoothly advances the dialog with the user. Dialog management device. Each dialog scenario is provided with one or more response conditions consisting of the attribute or the attribute value corresponding to the attribute, and each operation to be executed next when the response condition is satisfied. The above response action is defined,
The behavior determining means searches the dialog scenario database that matches the response condition using the attribute or the attribute value of the user corresponding to the attribute, and searches the dialog scenario database for the searched scenario. The dialog management device according to claim 1 or 2, wherein the response action corresponding to the response condition is determined as a next action. Among the response actions of each of the dialog scenarios, there is a response action including continuation of the response of the dialog scenario or termination of the dialog scenario,
The behavior determination means, when the response action according to the attribute or the attribute value of the searched dialogue scenario is a continuation of the response of the dialogue scenario or the end of the dialogue scenario, The dialogue management device according to claim 1, wherein the dialogue management device continues or terminates the scenario.   When the behavior determining means searches the dialog scenario database for one or more dialog scenarios that match the attribute or the attribute value of the user for the attribute, after searching from the special scenario, the normal The dialogue management apparatus according to claim 2, wherein a search is performed from a scenario.   Priorities are given to each of the conversation scenarios, and when the action determining means searches for a plurality of the conversation scenarios, the conversation control means, according to the priorities assigned to the respective conversation scenarios, 6. The dialogue management apparatus according to claim 1, wherein the dialogue action device executes the response action of the dialogue scenario. An interactive scenario in which a plurality of interactive scenarios in which an attribute of information and a response action according to the information attribute are set, and an interactive scenario in which a response action according to the attribute value for the information attribute and the information attribute is set are stored A database, scenario selection means, response generation means, action determination means, and dialogue control means;
A scenario selection step in which the scenario selection means selects an interaction scenario of the attribute from the interaction scenario database based on the attribute of the information requested from the information request means;
A response generation step in which the response generation unit generates a response sentence when the response sentence is described in the response action corresponding to the attribute of the dialogue scenario selected by the scenario selection unit, and gives the response sentence to the user terminal;
Based on the user response sentence that the behavior answering means answers from the user to the response sentence, the action determining means receives the attribute value that the user is aware of for the attribute obtained by analyzing the answer sentence analyzing means, and matches the attribute value of the user for the attribute An action determination step of searching for one or more interaction scenarios to be performed from the interaction scenario database, and determining a response action corresponding to the attribute value for the attribute set in any of the interaction scenarios as the next action;
A dialogue control means for carrying out dialogue control according to the next action determined by the action determination means;
The dialogue control means
When a response sentence set in advance to be given to the user terminal is described in the response action related to the next action, the response sentence is generated by the response generation means, and the response sentence is requested to be given to the user terminal. And
When an attribute of another interaction scenario to be called next is described in the response action related to the next action, the scenario selection unit requests the other interaction scenario having the attribute described in the response action to be selected. A dialogue management method characterized by that. An interactive scenario in which a plurality of interactive scenarios in which an attribute of information and a response action according to the information attribute are set, and an interactive scenario in which a response action according to the attribute value for the information attribute and the information attribute is set are stored A computer with a database,
A scenario selection means for selecting a dialogue scenario of the attribute from the dialogue scenario database based on the attribute of the information requested from the information requesting means;
A response generating means for generating a response sentence and giving the response sentence to the user terminal when a response sentence is described in the response action corresponding to the attribute of the dialogue scenario selected by the scenario selecting means;
One or a plurality of attribute values that the user is aware of for the attribute obtained by analyzing the answer sentence analysis means based on the user answer sentence answered by the user with respect to the response sentence, and match the attribute value of the user for the attribute An action determination unit that searches for an interaction scenario from an interaction scenario database and determines a response action corresponding to the attribute value for the attribute set in one of the interaction scenarios as the next action;
It functions as a dialog control means that performs dialog control according to the next action determined by the action determination means,
The dialogue control means
When a response sentence that is set in advance for the user terminal is described in the response action related to the next action, the response generator generates the response sentence and requests that the response sentence be given to the user terminal And
When an attribute of another interaction scenario to be called next is described in the response action related to the next action, the scenario selection unit requests the other interaction scenario having the attribute described in the response action to be selected. Dialog management program characterized by that. A plurality of interaction scenarios including an interaction scenario in which an attribute of information and a response action corresponding to the attribute of information are set, and an interaction scenario in which a response action according to an attribute value of the information attribute and the information attribute is set And a response management device for giving a response message to the user terminal, receiving a user answer message for the response message from the user terminal, and interacting with the user;
An answer sentence analysis device for analyzing an attribute value perceived by the user for an attribute based on the user answer sentence received from the user terminal;
A dialogue information accumulating device for accumulating for each user a user attribute value for the attribute for each dialogue scenario;
A consciousness extraction system, wherein the dialogue management device corresponds to the dialogue management device according to any one of claims 1 to 6.

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