WO2020234948A1

WO2020234948A1 - Information output device, information output method, and program

Info

Publication number: WO2020234948A1
Application number: PCT/JP2019/019800
Authority: WO
Inventors: 基光白川
Original assignee: ソプラ株式会社
Priority date: 2019-05-17
Filing date: 2019-05-17
Publication date: 2020-11-26
Also published as: JPWO2020234948A1; JP6598418B1

Abstract

[Problem] Conventionally, it has been difficult to receive conversational sentences that dynamically change even for inquiries that require the same search result, and retrieve information. [Solution] An information output device comprising: a conversational sentence reception unit for receiving a conversational sentence; an intent determination unit for determining an intent corresponding to the conversational sentence; a conversational sentence information determination unit for determining conversational sentence information that is closest to the conversational sentence from among one or more pieces of conversational sentence information corresponding to the intent; an entity acquisition unit for acquiring one or more entities that correspond to one or more entities associated with the conversational sentence information and that are words in the conversational sentence; a parameter acquisition unit for acquiring one or more parameters corresponding to the one or more entities; an API information acquisition unit for acquiring API information corresponding to the intent; an inquiry information constitution unit for constituting inquiry information by using the one or more parameters and the API information; a search unit for executing the inquiry information to acquire a search result; and a search result output unit.

Description

Information output device, information output method, and program

The present invention relates to an information output device or the like that accepts conversational sentences, searches a database in an organization such as a company for information, and outputs the results.

Conventionally, in order to search information for a database in an organization, for example, a technique of creating a dedicated program or acquiring information from the database using a search tool and outputting it has been used.
Further, in recent years, there has been a technique for searching the Internet or turning on / off a predetermined device by a word uttered by a user (see, for example, Non-Patent Document 1).

However, conversational sentences (which may be called natural language sentences) change dynamically even for inquiries that request the same search results, depending on, for example, the person who issues them or the organization of the company to which the person belongs. For example, there are many conversational sentences that inquire about the overtime hours of a specific employee in a specific month, such as "Tell me about Nakamura's overtime hours last month" and "Tell me about Nakamura's overtime hours last month." To do.

With the above-mentioned conventional technology, it was difficult to accept dynamically changing conversational sentences and search for information even with such inquiries requesting the same search results.

The information output device of the first invention is an intent storage unit that stores one or more intents that are information managed for each business process and have an action name that specifies the business process. An API information storage unit that stores one or more API information, which is information corresponding to a tent, information for performing an information search, and information having information for specifying a parameter which is one or more variables. , A corpus storage unit that stores one or more conversational text information that is information corresponding to the intent and is conversational text information, and one or more entities that are words that correspond to any one or more conversational text information. The entity storage unit to be stored, the conversation sentence reception unit that accepts conversation sentences, the intent determination unit that determines the intent corresponding to the conversation sentence received by the conversation sentence reception unit, and the intent determined by the intent determination unit. From one or more conversational sentence information corresponding to, the conversational sentence information determination unit that determines the conversational sentence information that most closely resembles the conversational sentence received by the conversational sentence reception unit, and the conversational sentence information determined by the conversational sentence information determination unit. An entity acquisition unit that acquires one or more entities that are words possessed by the conversational sentence received by the conversation sentence reception unit, and one or more entities that the entity acquisition unit has acquired, corresponding to each of the one or more entities associated with. The parameter acquisition unit that acquires one or more parameters corresponding to the entity, the API information acquisition unit that acquires the API information corresponding to the intent determined by the intent determination unit from the API information storage unit, and the parameter acquisition unit have acquired it. Using one or more parameters and the API information acquired by the API information acquisition unit, the inquiry information configuration unit that constitutes the inquiry information for information retrieval and the inquiry information configured by the inquiry information configuration unit It is an information output device including a search unit that executes and acquires a search result, and a search result output unit that outputs the search result acquired by the search unit.

With this configuration, it is possible to accept dynamically changing conversational sentences and search for information even with inquiries requesting the same search results.

Further, in the information output device of the second invention, with respect to the first invention, the intent determination unit acquires the text corresponding to the conversation sentence received by the conversation sentence reception unit, and one or more independence from the text. It is an information output device that acquires a word and determines an intent having an action name having a word that is the same as or similar to one or more independent words.

With this configuration, it is possible to accept dynamically changing conversational sentences and search for information even with inquiries that request the same search results.

Further, the information output device of the third invention is information about a day word which is a word related to a day and a day corresponding to the day word for the first or second invention, and constitutes inquiry information. A day conversion information storage unit for storing one or more day conversion information having a day information acquisition information for acquiring day information which is information used at the time is further provided, and the parameter acquisition unit is an entity acquisition unit. It is an information output device that acquires day conversion information corresponding to a day word in one or more acquired entities from the day conversion information storage unit, and acquires day information as a parameter by using the day conversion information.

With such a configuration, it is possible to accept dynamically changing conversational sentences even for inquiries requesting the same search results, and to appropriately search for information.

In the above configuration, the parameter acquisition unit determines whether or not the day word exists in one or more entities acquired by the entity acquisition unit, and the determination means 341 determines that the day word exists. In this case, the day conversion information corresponding to the day word may be acquired from the day conversion information storage unit, and the day information acquisition means for acquiring the day information which is a parameter may be provided by using the day conversion information. As a result, it is possible to accept dynamically changing conversational sentences even in a query for the same search result regardless of the presence or absence of a Japanese word, and to appropriately search for information.

Further, in the information output device of the fourth invention, for any one of the first to third inventions, the entity of the entity storage unit corresponds to the entity name which is the name of the entity, and the table is specified. An entity that stores one or more entity mapping information having a translated item name and an entity name, which are the table identifier to be used, the attribute name in the table identified by the table identifier, and the information that identifies the entity to be converted. It further includes a mapping information storage unit and a PK item storage unit that stores one or more PK items having a table identifier and a primary key identifier that identifies the primary key of the table identified by the table identifier, and is a parameter acquisition unit. Is a translation item that acquires the entity name acquisition means that acquires the entity name corresponding to the entity acquired by the entity acquisition unit and the translation item name that is paired with the entity name acquired by the entity name acquisition unit from the entity mapping information storage unit. The name acquisition means, the table identifier acquisition means that acquires the table identifier that is paired with the entity name acquired by the entity name acquisition means from the entity mapping information storage unit, and the primary key that is paired with the table identifier acquired by the table identifier acquisition means. The attribute value of the translation item name acquired by the translation item name acquisition means is the entity acquisition from the table identified by the primary key identifier acquisition means that acquires the identifier from the PK item storage unit and the table identifier acquired by the table identifier acquisition means. Information output including a conversion parameter acquisition means for acquiring a converted parameter which is an attribute value included in a record matching the entity acquired by the unit and is an attribute value of the primary key identifier acquired by the primary key identifier acquisition means. It is a device.

Further, in the information output device of the fifth invention, for any one of the first to fourth inventions, the inquiry information component unit is one or more variables contained in the API information acquired by the API information acquisition unit. This is an information output device that configures inquiry information by arranging the parameters that correspond to each location and the parameters acquired by the parameter acquisition unit.

Further, in the information output device of the sixth invention, for any one of the first to fifth inventions, the reception unit performs voice reception means for receiving the voice of the conversation sentence and voice recognition processing for the voice. It is an information output device including a voice recognition means for acquiring a conversational sentence which is a character string.

With this configuration, it is possible to accept dynamically changing voice conversation sentences and search for information even with inquiries requesting the same search results.

According to the present invention, it is possible to accept dynamically changing conversational sentences and search for information even with an inquiry requesting the same search result.

Block diagram of the information output device according to the embodiment Flow chart explaining the operation of the information output device Flowchart explaining parameter acquisition process Data structure diagram of table information Intent data structure diagram The figure which shows an example of the contents of the API information storage part The figure which shows the figure which shows an example of the contents of the corpus storage part Diagram showing an example of one or more entities corresponding to each entity name Data structure diagram of entity mapping information Data structure diagram of PK items External view of computer system Diagram showing an example of the internal configuration of a computer system

Hereinafter, embodiments of the information output device and the like will be described with reference to the drawings. In the embodiment, the components with the same reference numerals perform the same operation, and thus the description may be omitted again.

The information output device in this embodiment is, for example, a server. The server is, for example, a server in a company that provides services such as information retrieval, but may be a cloud server, an ASP server, or the like, and its type does not matter. The server is communicably connected to one or more terminals (not shown) via a network such as a LAN or the Internet, a wireless or wired communication line, or the like. The terminal is, for example, a mobile terminal of a user who uses a service such as information retrieval, but may be a stationary PC or the like, and the type is not limited. The mobile terminal is, for example, a tablet terminal, a smartphone, a mobile phone, a notebook PC, or the like, but the type is not limited.

However, the information output device may be, for example, a stand-alone terminal, and the means for realizing it does not matter.

FIG. 1 is a block diagram of an information output device according to the present embodiment. The information output device includes a storage unit 1, a reception unit 2, a processing unit 3, and an output unit 4. The storage unit 1 includes a table storage unit 11, an intent storage unit 12, an API information storage unit 13, a corpus storage unit 14, an entity storage unit 15, an entity mapping information storage unit 16, a PK item storage unit 17, and a day conversion information storage unit. The unit 18 is provided. The reception unit 2 includes a conversation text reception unit 21. The conversation sentence reception unit 21 includes a voice reception means 211 and a voice recognition means 212.

The processing unit 3 includes an intent determination unit 31, a conversation sentence information determination unit 32, an entity acquisition unit 33, a parameter acquisition unit 34, an API information acquisition unit 35, an inquiry information configuration unit 36, and a search unit 37. The parameter acquisition unit 34 includes a determination unit 341, a day information acquisition unit 342, an entity name acquisition unit 343, a translation item name acquisition unit 344, a table identifier acquisition unit 345, a primary key identifier acquisition unit 346, and a conversion parameter acquisition unit 347. .. The output unit 4 includes a search result output unit 41.

The storage unit 1 can store various types of information. The various types of information include, for example, tables, intents, API information, corpora, entities, entity mapping information, PK items, and day conversion information. Information on tables and the like will be described later. In addition, other information will be explained in a timely manner.

One or two or more tables are stored in the table storage unit 11. The table may be, for example, a tabular database. For example, one or more item names are registered in the table, and one or two or more values are registered for each of the one or more item names. The item name may be referred to as an attribute name, and each value of 1 or more corresponding to one item name may be referred to as an attribute value. The table is, for example, a relational database table, TSV, Excel, CSV, or the like, but the type is not limited.

Specifically, the stored table is, for example, an employee master, a business master, a working time table, or the like. Master data about employees is registered in the employee master. The master data related to an employee is, for example, data such as an employee code and an employee name, but the type does not matter. Master data related to the business is registered in the business master. The master data related to the business is, for example, data such as a business ID and a business name, but the type thereof does not matter.

Data related to working hours are registered in the working hours table. The data related to working hours is, for example, variable data such as date, overtime hours, total working hours, business ID, etc., but the type is not limited. The total working hours is the total of working hours up to the scheduled time and overtime hours.

Normally, data related to working hours as described above is registered in the working hours table in association with the employee code. However, the information to which the data on working hours is associated may be, for example, an employee name, or any information that can identify the employee.

One or two or more intents are stored in the intent storage unit 12. An intent is information managed for each business process. The management for each business process may be, for example, stored in the intent storage unit 12 in association with the information that identifies the business process. The information that identifies the business process is usually the action name described later, but the format does not matter. Correspondence also includes, for example, the case where the intent has information that identifies the business process.

Business processing is processing related to business. It can be said that the work is, for example, a work performed by an organization such as a company or an organization. The work includes, for example, work until the fixed time, overtime after the fixed time, vacation, absenteeism, A case, B case, accounting, manufacturing, etc., but the type does not matter. The business process is, for example, information retrieval. The search may be referred to as an inquiry, for example. The information to be searched is, for example, attendance information such as overtime hours and working hours, but may be financial information such as balances and stock prices, or operating conditions of manufacturing lines, and the contents thereof are not limited.

However, the business processing may be, for example, registration of information or processing based on information (for example, payroll calculation based on attendance information, financial transaction based on financial information, etc.), and the type does not matter.

The intent usually has an action name that identifies the business process. The action name is the name of the action. An action is a business process that is usually executed via an API. However, the action may be, for example, a business process executed in response to an SQL statement.

Note that the action name usually corresponds to the API information described later. Therefore, it may be considered that the intent is associated with the API information, for example, via the action name.

Intents also usually have an intent name. The intent name is the name of the intent. Therefore, the intent can be considered as information that associates the intent specified by the intent name or the intent name with the action name or the action specified by the action name.

Specifically, the action name is, for example, "overtime hour inquiry", "working hour data inquiry", etc., but any information that can identify the business process may be used.

One or two or more API information is stored in the API information storage unit 13. API information is information about API. The API is an interface for using the functions of the program. An API is software such as a function, method, or execution module, for example. The API is, for example, WebAPI, but other APIs may be used. A Web API is an API constructed by using a Web communication protocol such as HTTP or HTTPS. Since APIs such as WebAPI are known techniques, detailed description thereof will be omitted.

API information is information that corresponds to the intent. As described above, the API information corresponds to the intent, for example, through the action name.

API information is usually information for performing information retrieval. However, the API information may be, for example, information for registering information or performing processing based on the information.

API information has one or more parameter specific information. The parameter specific information is information for specifying a parameter. It may be said that the parameter is a value having a specific attribute. The value is usually a variable. Variables may be called arguments.

The parameter is usually the information obtained by converting the entity, but it may be the entity itself. The parameters are, for example, arguments given to the API or variables in the SQL statement.

The parameter may be composed of, for example, a set of an attribute name and a value. Specifically, the set of the attribute name and the value is, for example, "shain_code = 2", "sta_date = 2019041, end_date = 20190430", but the format does not matter.

The parameter specific information is, for example, a parameter name. The parameter name is the name of the parameter. Alternatively, the parameter-specific information is, for example, an attribute name, but any information that can specify the parameter may be used.

API information is, for example, a method. The methods are, for example, "search_overtime hours (employee code = $ 1, start date = $ 2, end date = $ 3)" and "search_business hours (employee code = $ 1, work date = $ 2, business ID =)". $ 3) "etc., but the format does not matter. Since the method is known, detailed description thereof will be omitted.

Alternatively, the API information may be, for example, an SQL statement. It can be said that the SQL statement is a statement for making an inquiry to the database. The SQL statement is, for example, "select_overtime_from_table name = $ 1_where_employee code = $ 2, business date = $ 3", but the structure does not matter. Since the SQL statement is well known, detailed description thereof will be omitted.

Alternatively, the API information may be, for example, a set of a URL and a method, and its structure does not matter. Specifically, the set of the URL and the method is, for example, "http://develop.soppra ...? Employee code = $ 1 & start date = $ 2 & end date = $ 3". Does not matter. Note that this type of API information may be referred to as, for example, Web API information.

One or more conversational sentence information is stored in the corpus storage unit 14. Conversational sentence information is information on conversational sentences. The conversational sentence information is usually an example sentence of a conversational sentence. Example sentences are, for example, "Tell me about Nakamura's overtime hours last month" and "Tell me about Nakamura's working hours for yesterday's A project", but the content does not matter.

However, the conversation text information may be a conversation text template. The template is, for example, "Tell me {Overtime entity} of {Date entity} of {Employee entity}" or "Tell me {Working time entity} of {Business entity} of {Date entity} of {Employee entity}". Etc., but the format does not matter. Information expressed by "{", "}" such as {employee entity} included in the template may be called a variable, for example. Further, the entity and the entity name such as "employee entity" will be described later.

Conversational text information usually corresponds to the intent. That is, in the corpus storage unit 14, for example, one or two or more conversational sentence information is stored for each one or more intents stored in the intent storage unit 12 (see FIG. 7: described later).

In addition, the corpus storage unit 14 usually stores one or more entity information for each one or more stored conversational sentence information. The entity information is information about one or more entities corresponding to one conversational sentence information. The entity information has, for example, an entity, a start position, an end position, and an entity name when the conversational sentence information is an example sentence.

The entity possessed by the entity information is a representative value among one or two or more entities corresponding to the entity name possessed by the entity information. The representative value is, for example, the first entity in one or more entities corresponding to one entity name, but any entity may be used.

The start position is the position where the entity starts in the conversation text information. The start position is represented by, for example, a value (for example, "1", "4", etc.) indicating which character the first character of the entity is in the character string constituting the conversation sentence. Similarly, the end position is a position where the entity ends in the conversation text information, and is, for example, a value indicating the number of the last character of the entity (for example, "2", "5", etc.). ). However, the expression format of the start position and the end position does not matter. The start position and end position may be referred to as offsets. Further, the offset may be expressed by the number of bytes, and its format does not matter.

The entity name is the name of the entity. The entity name is, for example, "employee entity", "date entity", "overtime hour entity", etc., but the format is not limited as long as it is information that can express the attributes of the entity. An employee entity is an entity related to an employee. A date entity is an entity related to a date. The overtime hours entity is an entity related to overtime hours.

Alternatively, when the conversation text information is a template, the entity information may have, for example, an entity name and order information. The order information is a value indicating which variable the entity name corresponds to in one or more variables included in the template. However, the structure of the entity information does not matter.

Specifically, in the corpus storage unit 14, for example, conversational sentence information "Tell me about Nakamura's overtime hours last month" and three corresponding entity information "Nakamura, 1, 2, employee entity", " Last month, 4, 5, date entities "and" overtime hours, 7, 10, overtime entities "may be stored.

The corpus in the present embodiment may be considered as, for example, each of one or more conversational sentence information stored in the corpus storage unit 14, one or more conversational sentence information, and each conversational sentence information. It can also be thought of as a set of associated entity information.

One or two or more entities are stored in the entity storage unit 15. An entity is one or more words associated with conversational sentence information. A word is a unit that makes up a sentence. A word may be simply called, for example, a "word" or a "word", or may be considered as a kind of morpheme (for example, an independent word described later).

In the entity storage unit 15, for example, one or two or more entities are stored in association with each one or more entity names.

The entity usually corresponds to any one or more conversational sentence information in one or more conversational sentence information stored in the corpus storage unit 14. Therefore, for example, one or more entities may be stored in the entity storage unit 15 for each one or more conversational sentence information stored in the corpus storage unit 14.

The word corresponding to the conversational sentence information is usually an independent word. An independent word is a word that can form a phrase by itself, and is, for example, a noun, but may also be a verb, an adjective, or the like. However, the corresponding word may be an attached word. An adjunct word is a word that cannot form a phrase by itself and that forms a phrase with other independent words, such as auxiliary verbs and particles. That is, the corresponding word is usually an independent word, but may be an independent word with an adjunct.

Also, the corresponding words may be, for example, collocations. A collocation is a word that expresses a certain meaning by connecting two or more autonomous words, and may be called a compound word. The collocations are, for example, "overtime hours" in which "overtime" and "hours" are combined, "A project" in which "A" and "project" are combined, etc., but a group named "Ichiro Nakamura". However, any set of two or more words may be used.

When the conversational sentence information is an example sentence, the corresponding words are one or more words (that is, the information in the conversational sentence information) included in the example sentence, but when the conversational sentence information is a template. Is a word (that is, information added to conversational sentence information) to be inserted at the position of one or more variables included in the template.

One or two or more entity mapping information is stored in the entity mapping information storage unit 16. It can be said that the entity mapping information is information that associates the table identifier and the translated item name with the entity name.

The entity mapping information has, for example, a table identifier, a translation item name, and an entity name. The table identifier is information for identifying one or more tables stored in the table storage unit 11. The table identifier is, for example, "MST_SHAIN" or "TRN_TIME_CARD", but any information that can identify the table may be used.

The translation item name is an attribute name in the table identified by the table identifier, and is information that identifies the entity to be translated. The converted entity is the entity converted to the parameter (for example, the entity "Ichiro Nakamura" converted to the parameter "shain_code = 1" and the entity "last month" converted to the parameter "sta_date = 2019041, end_date = 20190430". "Etc.).

The translated item name is, for example, an item name corresponding to a key other than the primary key among one or more item names of the table identified by the table identifier, and the item name to be converted into the item name corresponding to the primary key. It may be. The item name corresponding to the primary key is, for example, a primary key identifier.

The translation item name is, for example, "SHAIN_CODE" or "TIME_CARD_DATE", but any information that can identify the entity to be converted may be used.

One or two or more PK items are stored in the PK item storage unit 17. The PK item is an item corresponding to the primary key. The PK item has, for example, a table identifier and a primary key identifier. The primary key identifier is information that identifies the primary key of the table identified by the table identifier.

The primary key identifier is, for example, "SHAIN_CODE" in the case of a table identified by the table identifier "MST_SHAIN" (hereinafter, employee master), and is a table (hereinafter, working hours table) identified by the table identifier "TRN_TIME_CARD". There are two cases, "SHAIN_CODE" and "TIME_CARD_DATE".

One or more day conversion information is stored in the day conversion information storage unit 18. The day conversion information is information for converting a day word into a date. A day word is a word about a day. The day word is usually a word associated with the entity name "date entity", for example, "last month", "yesterday", "last week", "this year", "this month", "last year", "previous term", For example, "this year", but any information that can be converted into a date may be used.

The day conversion information includes a day word and day information acquisition information. The daily information acquisition information is information for acquiring the daily information. The day information is information about the day corresponding to the day word, and is information used when constructing inquiry information. The day information may be, for example, information indicating a date such as "April 1" or information indicating a period from the start date to the end date such as "4/1 to 4/30", and the format thereof is It doesn't matter. The day information acquisition information is, for example, a function name or a method name, but may be API information or the program itself, and its format does not matter.

Specifically, as the day information acquisition information for the day word "last month", for example, the current time information (for example, "May 10, 2019 11:15": the same applies hereinafter) is acquired, and the current time information has the information. Acquire the previous month (for example, "April") for the month (for example, "May"), refer to the calendar information of the previous month, and perform the day information (for example, the first day to the last day of the previous month). For example, a program or the like for acquiring "4/1 to 4/30" etc. may be used.

Further, the day information acquisition information for the day word "this year" is, for example, from the first day of the year by acquiring the current time information and referring to the calendar information of the year (for example, "2019") that the current time information has. , API information or the like for acquiring day information (for example, “2019/1/1 to 2019/5/10”) up to the date of the current time information.

Further, the day information acquisition information for the day word "yesterday" is a method of acquiring the current time information and acquiring the day information (for example, "5/9") of the day before the day of the current time information, or The method name or the like may be used.

Reception department 2 receives various information. The various types of information are, for example, conversational sentences. The reception unit 2 receives information such as conversational sentences from, for example, a terminal, but may receive information via an input device such as a keyboard, a touch panel, or a microphone. Alternatively, the reception unit 2 may accept information read from a recording medium such as a disk or a semiconductor memory, and the mode of acceptance is not limited.

The conversation sentence reception unit 21 accepts conversation sentences. A conversational sentence is a sentence in which a person speaks, and can be said to be a sentence in natural language. Conversational sentences are accepted, for example, by voice, but may be accepted by text. A voice is a voice made by a person. A text is a character string that voice-recognizes a voice uttered by a person. A character string is composed of an array of one or more characters.

The voice receiving means 211 receives the voice of the conversational sentence. The voice receiving means 211 receives the voice of the conversational sentence from the terminal, for example, in pairs with the terminal identifier, but may receive the voice through the microphone. The terminal identifier is information that identifies a terminal. The terminal identifier is, for example, a MAC address, an IP address, an ID, or the like, but any information that can identify the terminal may be used. The terminal identifier may be a user identifier that identifies the user of the terminal. The user identifier is, for example, an e-mail address, a telephone number, or the like, but may be an ID, an address, a name, or the like, and may be any information that can identify the user.

The voice recognition means 212 performs voice recognition processing on the voice received by the voice reception means 211, and acquires a conversational sentence which is a character string. The voice recognition process is a known technique, and detailed description thereof will be omitted.

The processing unit 3 performs various processes. The various processes include, for example, an intent determination unit 31, a conversation sentence information determination unit 32, an entity acquisition unit 33, a parameter acquisition unit 34, an API information acquisition unit 35, an inquiry information configuration unit 36, a search unit 37, and a determination means. 341, day information acquisition means 342, entity name acquisition means 343, translation item name acquisition means 344, table identifier acquisition means 345, primary key identifier acquisition means 346, conversion parameter acquisition means 347, and the like. Further, the various processes include, for example, various discriminations described in the flowchart.

The processing unit 3 processes, for example, the intent determination unit 31 and the like in response to the conversation sentence reception unit 21 receiving the conversation sentence. When a conversational sentence is transmitted from one or more terminals to a pair with the terminal identifier, the processing unit 3 performs processing of the intent determination unit 31 and the like for each one or more terminal identifiers.

The intent determination unit 31 determines the intent corresponding to the conversation sentence received by the conversation sentence reception unit 21.

Specifically, the intent determination unit 31 first acquires, for example, the text corresponding to the conversation sentence received by the conversation sentence reception unit 21. As described above, the text is, for example, the result of voice recognition of the conversation sentence received by the conversation sentence reception unit 21, but may be the conversation sentence itself received by the conversation sentence reception unit 21.

That is, when the intent determination unit 31 receives a conversational sentence that is voice, the intent determination unit 31 voice-recognizes the conversational sentence and acquires the text. When the conversational sentence which is a text is accepted, the intent determination unit 31 may acquire the text.

Next, the intent determination unit 31 acquires one or more independent words from the acquired text by, for example, performing morphological analysis on the acquired text. The morphological analysis is a known technique, and detailed description thereof will be omitted.

Then, the intent determination unit 31 determines an intent having an action name having a word that is the same as or similar to the acquired one or more independent words.

For details, for example, a synonym dictionary is stored in the storage unit 1. A synonym dictionary is a dictionary related to synonyms. In the synonym dictionary, the word possessed by the action name and one or more synonyms of the word are registered for each action name constituting one or more intents stored in the intent storage unit 12. ing. Specifically, for example, "overtime", "overtime hours", and the like may be registered in association with the word "overtime hours" of the action name "overtime hours inquiry".

For example, when the conversation sentence reception unit 21 accepts the conversation sentence "Tell me about the overtime hours of Otsuka last month", the intent determination unit 31 will use the conversation sentence "Otsuka", "last month", or "overtime hours". Etc. is acquired, and the intent storage unit 12 is searched using each independent word as a key, and it is determined whether or not there is an intent having an action name that matches the independent word. The match is, for example, an exact match, but may be a partial match. Then, when there is an intent having an action name having a word matching the independent word, the intent determination unit 31 determines the intent. In this example, since there is an intent having the action name "overtime hours reference" having the word "overtime hours" matching the independent word "overtime hours", the intent is determined.

If there is no intent having an action name having a word that matches the independent word, for example, the intent determination unit 31 refers to one synonym from one or more synonyms corresponding to the independent word from the synonym dictionary. Is acquired, the intent storage unit 12 is searched using the one synonym as a key, and it is determined whether or not there is an intent having an action name having a word matching the one synonym. Then, when there is an intent having an action name having a word matching the one synonym, the intent determination unit 31 determines the intent. If there is no such intent, the intent determination unit 31 performs the same processing for other synonyms to determine the intent. For any synonym, if there is no such intent, the intent determination unit 31 may output that the intent is not determined.

The conversation sentence information determination unit 32 searches the corpus storage unit 14 using the intent determined by the intent determination unit 31 as a key, and the conversation sentence reception unit 21 is selected from one or more conversation sentence information corresponding to the intent. Determines the conversational sentence information that most closely resembles the conversational sentence received by.

The conversational sentence information that most closely resembles the conversational sentence is, for example, the conversational sentence information that has the highest degree of similarity to the conversational sentence. That is, the conversation sentence information determination unit 32 calculates, for example, the degree of similarity between the received conversation sentence and one or more conversation sentence information corresponding to the determined intent, and the conversation sentence information having the maximum similarity degree. To decide.

Alternatively, the conversation sentence information determination unit 32 may search for a conversation template that matches the template in which the position of the noun of the accepted conversation sentence is used as a variable. That is, the corpus storage unit 14 stores a template in which one or two or more entity names are used as variables, and the conversation sentence information determination unit 32 stores one or two or more entity names of the accepted conversation sentence. Acquires the position of, and determines the template corresponding to the position of the acquired entity name as conversational sentence information. The position of one or more entity names in the conversation sentence is information indicating the number of the entity name in the template having one or more entity names.

The entity acquisition unit 33 corresponds to one or more entities corresponding to the conversation sentence information determined by the conversation sentence information determination unit 32, and is one or more words possessed by the conversation sentence received by the conversation sentence reception unit 21. Get an entity.

For example, the entity acquisition unit 33 acquires the start position and end position of the entity from the corpus storage unit 14 for each one or more entities corresponding to the determined conversational sentence information, and from the received conversational sentence. , Gets the word specified by the start position and the end position.

Specifically, as described above, for example, the conversation text information "Tell me about Nakamura's overtime hours last month" and the corresponding three entity information "Nakamura, 1, 2 and employees" are sent to the corpus storage unit 14. "Entity", "last month, 4, 5, date entity", and "overtime hours, 7, 10, overtime entity" are stored, and the conversation sentence reception department 21 tells the conversation sentence "Otsuka's overtime hours last month. When the conversation text information determination unit 32 determines the above conversation text information "Tell me the overtime hours of Nakamura last month", the entity acquisition department 33 determines the accepted conversation text "Otsuka's overtime hours last month". From "Tell me", the word "Otsuka" specified by the start position "1" and the end position "2" of the first entity information, and the start position "4" and the end position of the second entity information. The word "last month" specified by "5" and the word "overtime hours" specified by the start position "7" and the end position "10" of the third entity information are acquired.

The parameter acquisition unit 34 acquires one or more parameters corresponding to one or more entities acquired by the entity acquisition unit 33.

The acquired parameter is, for example, the acquired entity itself, but it may be information obtained by converting the acquired entity. That is, for example, when the acquired day word is included in one or more entities, the parameter acquisition unit 34 converts the day word into the parameter day information.

The determination means 341 constituting the parameter acquisition unit 34 determines whether or not the day word exists in one or more entities acquired by the entity acquisition unit 33. Specifically, for example, one or two or more day words are stored in the storage unit 1, and the determination means 341 matches any of the stored day words for each of the acquired one or more entities. It is determined whether or not to do so, and when the determination results for at least one entity show a match, it is determined that the day word exists in the acquired one or more entities.

When the determination means 341 determines that the day word exists in one or more acquired entities, the day information acquisition means 342 acquires the day conversion information corresponding to the day word from the day conversion information storage unit 18. , The day information which is a parameter is acquired by using the day conversion information.

Specifically, for example, the day word "last month" and the like are stored in the storage unit 1, and the conversational sentence "Tell me the overtime hours of last month of Otsuka" is accepted, and the three entities "Otsuka" and " When "last month" and "overtime hours" are acquired, the determination means 341 determines that the day word exists among the acquired 3 entities because the entity "last month" matches the day word "last month". To do. For example, the current time information is acquired and the day information (for example, "4/1 to 4/30") is acquired.

The day information acquisition means 342 acquires the day information acquisition information (for example, a program) corresponding to the day word "last month" from the day conversion information storage unit 18. Then, the day information acquisition means 342 acquires the current time information (for example, "May 10, 2019 11:15") from the built-in clock of the MPU, the NTP server, or the like by using the day information acquisition information, and the relevant day information acquisition means. Acquires the previous month (for example, "April") with respect to the month (for example, "May") that the current time information has. Then, the day information acquisition means 342 acquires the day information "April 1st to April 30th" from the first day to the last day of the previous month by referring to the calendar information of the previous month.

When the day word acquired from the conversation sentence is "this year", the day information acquisition means 342 stores the day information acquisition information (for example, API information) corresponding to the day word "this year" in the day conversion information storage unit. Obtained from 18. Then, the day information acquisition means 342 acquires the current time information from the built-in clock or the like by using the day information acquisition information, and refers to the calendar information of the year (for example, "2019") possessed by the current time information. , The day information (for example, "2019/1/1 to 2019/5/10") from the first day of the year to the day held by the current time information is acquired.

Further, when the acquired day word is "yesterday", the day information acquisition means 342 acquires the day information acquisition information (for example, a method) corresponding to the day word "yesterday" from the day conversion information storage unit 18. .. Then, the day information acquisition means 342 acquires the current time information from the built-in clock or the like by using the day information acquisition information, and the day information of the day before the day that the current time information has (for example, "5/9"). ”) Is acquired.

The entity name acquisition means 343 acquires the entity name corresponding to the entity from the entity storage unit 15 for each one or more entities acquired by the entity acquisition unit 33.

The entity name corresponding to the entity is an entity name paired with a start position and an end position that match or are similar to the position of the entity corresponding to the entity in the conversation sentence obtained by the entity. The entity name acquisition means 343 acquires the entity name corresponding to the entity from the entity storage unit 15 for each one or more entities acquired by the entity acquisition unit 33, for example, using the entity information associated with the entity. You may.

Specifically, for example, when the three entities "Otsuka", "Last month", and "Overtime hours" are acquired from the accepted conversation "Tell me the overtime hours of Otsuka last month", the entity name acquisition means. 343 was accepted among the three entity information stored in association with the conversational text information in the conversational text information "Tell me Nakamura's overtime hours last month" stored in the corpus storage unit 14. Using the first entity information that has the same start position "1" and end position "2" as "Otsuka" in the conversation "Tell me about Otsuka's overtime hours last month", "Nakamura" is associated with "Nakamura". Get "Employee Entity".

Further, for example, the entity name acquisition means 343 sets the same start position "4" and end position "5" as "last month" in the conversation sentence "Tell me the overtime hours of last month of Otsuka" among the above three entity information. Use the second entity information you have to get the "date entity" that corresponds to "last month", and the same start position as "overtime hours" in the conversation "Tell me about overtime hours last month in Otsuka". Using the third entity information having "7" and the end position "10", the "overtime hours entity" corresponding to the "overtime hours" is acquired.

The translation item name acquisition means 344 acquires, for example, a translation item name paired with the entity name from the entity mapping information storage unit 16 for each one or more entity names acquired by the entity name acquisition means 343.

Specifically, the entity mapping information storage unit 16 has, for example, an entity mapping information 1 having a table identifier "MST_SHAIN", a translation item name "SHAIN_NAME", and an entity name "employee entity", a table identifier "TRN_TIME_CARD", and a translation item. Entity mapping information 2 having the name "TIME_CARD_DATE" and the entity name "date entity", entity mapping information 3 having the table identifier "TRN_TIME_CARD", the translation item name "ZIKANGAI_TIME" and the entity name "overtime entity" are stored. When the entity name acquisition means 343 acquires the three entity names "employee entity", "date entity", and "overtime entity", the translation item name acquisition means 344 uses the three entity mapping informations 1 to 3. Translated item name "SHAIN_NAME" paired with the entity name "employee entity", translated item name "TIME_CARD_DATE" paired with the entity name "date entity", and translated item name paired with "overtime entity" Acquire "ZIKANGAI_TIM".

The table identifier acquisition means 345 acquires a table identifier paired with the entity name from the entity mapping information storage unit 16 for each one or more entity names acquired by the entity name acquisition means 343.

Specifically, the table identifier acquisition means 345 uses, for example, the above three entity mapping information 1 to 3 to form a table identifier "MST_SHAIN" paired with the entity name "employee entity" and an entity name "date entity". Acquire the paired table identifier "TRN_TIME_CARD" and the paired table identifier "TRN_TIME_CARD" with the entity name "overtime entity".

The primary key identifier acquisition means 346 acquires a primary key identifier paired with the table identifier acquired by the table identifier acquisition means 345 from the PK item storage unit 17.

Specifically, the PK item storage unit 17 has, for example, a PK item 1 having a table identifier "MST_SHAIN" and a primary key identifier "SHAIN_CODE", and a PK item having a table identifier "TRN_TIME_CARD" and a primary key identifier "SHAIN_CODE". 2. PK item 3 having the table identifier "TRN_TIME_CARD" and the primary key identifier "TIME_CARD_DATE", PK item 4 having the table identifier "MST_GYOUMU" and the primary key identifier "GYOUMU_ID", etc. are stored, and the primary key identifier Using the PK items 1 to 4, the acquisition means 346 uses the primary key identifier "SHAIN_CODE" paired with the table identifier "MST_SHAIN", the primary key identifier "SHAIN_CODE" paired with the table identifier "TRN_TIME_CARD", and the table identifier " Acquires the primary key identifier "TIME_CARD_DATE" paired with "TRN_TIME_CARD" and the primary key identifier "GYOUMU_ID" paired with the table identifier "MST_GYOUMU".

In the conversion parameter acquisition means 347, the attribute value of the translation item name acquired by the translation item name acquisition means 344 is the entity acquired by the entity acquisition unit 33 from the table identified by the table identifier acquired by the table identifier acquisition means 345. The converted parameter which is the attribute value included in the matching record and is the attribute value of the primary key identifier acquired by the primary key identifier acquisition means 346 is acquired.

Specifically, the conversion parameter acquisition means 347 has the attribute value of the translation item name “SHAIN_NAME” acquired from the employee master identified by the acquired table identifier “MST_SHAIN” as the acquired entity “Otsuka”. Acquires the converted parameter "shain_code = 2" which is an attribute value included in the matching record and is an attribute value of the acquired primary key identifier "SHAIN_CODE".

In addition, the conversion parameter acquisition means 347 is an entity in which the attribute values of the two translation item names "TIME_CARD_DATE" and "SHAIN_NAME" acquired from the working hours table identified by the acquired table identifier "TRN_TIME_CARD" are acquired. It is an attribute value included in the record that matches the entity "April 1st to April 30th" that converted "last month" and the acquired entity "Otsuka", and the two acquired primary key identifiers "SHAIN_CODE". And the converted parameter "shan_code = 2, sta_date = 2019041, end_date = 20190430" which is the attribute value of "TIME_CARD_DATE" is acquired.

The API information acquisition unit 35 acquires the API information corresponding to the intent determined by the intent determination unit 31 from the API information storage unit 13.

The API information acquisition unit 35 acquires, for example, API information having an action name corresponding to the intent determined by the intent determination unit 31 from the API information storage unit 13.

Specifically, in the API information storage unit 13, for example, the action name "overtime time inquiry" and three or more parameter specific information "employee code, share_code", "start date, sta_date", "end date, end_date", etc. API information 1 having the action name "working time data inquiry" and API information 2 having three or more parameter specific information "employee code, share_code", "work date, time_card_date", "business ID, gyoumu_id", etc. When the intent that is stored and is specified by the intent name "overtime inquiry intent" is acquired, the API information acquisition unit 35 has the API information 1 having the action name "overtime hour inquiry" that the intent has. To get.

The inquiry information configuration unit 36 configures inquiry information by using one or more parameters acquired by the parameter acquisition unit 34 and the API information acquired by the API information acquisition unit 35. Inquiry information is information for searching information, and is usually feasible information. The query information is, for example, a function or method in which an argument is inserted, but it may be a completed SQL statement or a set of URL and parameter.

The inquiry information configuration unit 36 is, for example, a parameter corresponding to each location at each of one or more variables of the API information acquired by the API information acquisition unit 35, and arranges the parameters acquired by the parameter acquisition unit 34. By doing so, inquiry information is constructed.

Specifically, for example, the inquiry information "https: /" in which "shain_code = 2", sta_date = 2019041 ", and end_date" = 20190430 are arranged at each of the three or more variables of the acquired API information 1. /Develop.soppra ...? Shan_code = 2 & sta_date = 2019041 & end_date = 20190430 "may be configured.

The search unit 37 executes the inquiry information configured by the inquiry information configuration unit 36 and acquires the search result. For example, the inquiry information "https://develop.soppra ...? Shanin_code = 2 & sta_date = 2019041 & end_date = 20190430" is executed, and the employee "Jiro Otsuka" specified by employee code 2 is executed from April 1 to April 30 Overtime hours "0401 = 1,0402 = 0, ... 4030 = 2" corresponding to each date up to the day may be acquired. Inquiry information such as SQL and detailed operations of the search unit 37 will be described with specific examples and modified examples.

The output unit 4 outputs various information. The various types of information are, for example, search results.

For example, the output unit 4 obtains information such as a search result, which is the result of various processing performed by the processing unit 3 in response to the reception unit 2 receiving information such as a conversation sentence in pairs with the terminal identifier. Send to the terminal identified by the identifier. Alternatively, for example, in response to the reception unit 2 receiving information such as a conversational sentence via an input device such as a touch panel or a microphone, the output unit 4 outputs information such as a search result to an output device such as a display or a speaker. It may be output via.

However, the output unit 4 may print out various types of information with a printer, store it in a recording medium, pass it on to another program, or transmit it to an external device, and the output unit 4 may output the output. The mode does not matter.

The search result output unit 41 outputs the search result acquired by the search unit 37. The search result output unit 41 transmits, for example, the search result acquired by the search unit 37 in response to the conversation sentence reception unit 21 receiving the conversation sentence in pairs with the terminal identifier to the terminal identified by the terminal identifier. .. Alternatively, the search result output unit 41 outputs, for example, the search result acquired by the search unit 37 in response to the conversation sentence reception unit 21 receiving the conversation sentence via an input device such as a microphone on a display, a speaker, or the like. It may be output via a device.

Storage unit 1, table storage unit 11, intent storage unit 12, API information storage unit 13, corpus storage unit 14, entity storage unit 15, entity mapping information storage unit 16, PK item storage unit 17, and day conversion information storage unit No. 18 is preferably a non-volatile recording medium such as a hard disk or a flash memory, but can also be realized by a volatile recording medium such as a RAM.

The process of storing information in the storage unit 1 etc. does not matter. For example, information may be stored in the storage unit 1 or the like via a recording medium, or information transmitted via a network, a communication line, or the like may be stored in the storage unit 1 or the like. Well, or the information input via the input device may be stored in the storage unit 1 or the like. The input device may be, for example, a keyboard, a mouse, a touch panel, a microphone, or the like.

The reception unit 2, the conversation text reception unit 21, the voice reception means 211, and the voice recognition means 212 may or may not include the input device. The reception unit 2 and the like can be realized by the driver software of the input device or by the input device and its driver software.

Processing unit 3, intent determination unit 31, conversational text information determination unit 32, entity acquisition unit 33, parameter acquisition unit 34, API information acquisition unit 35, inquiry information configuration unit 36, search unit 37, judgment means 341, day information The acquisition means 342, the entity name acquisition means 343, the translation item name acquisition means 344, the table identifier acquisition means 345, the primary key identifier acquisition means 346, and the conversion parameter acquisition means 347 can usually be realized from an API, a memory, or the like. The processing procedure of the processing unit 3 and the like is usually realized by software, and the software is recorded on a recording medium such as ROM. However, the processing procedure may be realized by hardware (dedicated circuit).

The output unit 4 and the search result output unit 41 may or may not include output devices such as displays and speakers. The output unit 4 and the like can be realized by the driver software of the output device, or by the output device and its driver software.

The receiving function of the reception unit 2 or the like is usually realized by a wireless or wired communication means (for example, a communication module such as a NIC (Network interface controller) or a modem), but a means for receiving a broadcast (for example, a broadcast). It may be realized by the receiving module). Further, the transmission function of the output unit 4 or the like is usually realized by a wireless or wired communication means, but may be realized by a broadcasting means (for example, a broadcasting module).

Next, the operation of the information output device will be described with reference to the flowcharts of FIGS. 2 and 3.

FIG. 2 is a flowchart illustrating the operation of the information output device. When a conversation sentence is transmitted from one or more terminals to a pair with a terminal identifier, the flowcharts of FIGS. 2 and 3 are executed for each one or more terminal identifiers.

(Step S201) The processing unit 3 determines whether or not the conversation sentence reception unit 21 has accepted the conversation sentence. If it is determined that the conversation sentence reception unit 21 has accepted the conversation sentence, the process proceeds to step S202, and if it is determined that the conversation sentence has not been accepted, the process returns to step S201.

(Step S202) The intent determination unit 31 determines an intent corresponding to the conversational sentence received in step S201 from one or more intents stored in the intent storage unit 12.

(Step S203) The conversation sentence information determination unit 32 determines the conversation sentence information most similar to the conversation sentence received in step S201 from one or more conversation sentence information corresponding to the intent determined in step S202. To do.

(Step S204) The entity acquisition unit 33 corresponds to each one or more entities corresponding to the conversational sentence information determined in step S203, and stores one or more entities of the conversational sentence received in step S201. Obtained from part 15.

(Step S205) The parameter acquisition unit 34 executes a process of acquiring one or more parameters corresponding to one or more entities acquired in step S204 (hereinafter, may be referred to as a parameter acquisition process). The parameter acquisition process will be described with reference to FIG.

(Step S206) The API information acquisition unit 35 acquires the API information corresponding to the intent determined in step S202 from the API information storage unit 13.

(Step S207) The inquiry information configuration unit 36 configures inquiry information by using one or more parameters acquired in step S205 and the API information acquired in step S206.

(Step S208) The search unit 37 executes the inquiry information configured in step S207 and acquires the search result.

(Step S209) The search result output unit 41 outputs the search result acquired in step S208. After that, the process returns to step S201.

In the flowchart of FIG. 2, the process starts when the power of the information output device is turned on or the program is started, and the process ends when the power is turned off or an interrupt for the end of the process occurs. However, the trigger for the start or end of processing does not matter.

FIG. 3 is a flowchart illustrating the parameter acquisition process in step S205.

(Step S301) The parameter acquisition unit 34 sets the initial value 1 in the variable i. The variable i is a variable for sequentially selecting unselected entities from the one or more entities acquired in step S204.

(Step S302) The parameter acquisition unit 34 determines whether or not there is an i-th entity. If it is determined that there is an i-th entity, the process proceeds to step S303, and if it is determined that there is no i-th entity, the process returns to higher processing.

(Step S303) The entity name acquisition means 343 acquires the entity name corresponding to the i-th entity from the entity storage unit 15.

(Step S304) The translation item name acquisition means 344 acquires the translation item name paired with the entity name acquired in step S303 from the entity mapping information storage unit 16.

(Step S305) The table identifier acquisition means 345 acquires a table identifier paired with the entity name acquired in step S303 from the entity mapping information storage unit 16.

(Step S306) The primary key identifier acquisition means 346 acquires a primary key identifier paired with the table identifier acquired in step S305 from the PK item storage unit 17.

(Step S307) The determination means 341 determines whether or not the i-th entity is a day word. If the i-th entity is determined to be a day word, the process proceeds to step S308, and if it is determined that the entity is not a day word, the process proceeds to step S309.

(Step S308) The day information acquisition means 342 acquires the day conversion information corresponding to the day word from the day conversion information storage unit 18, and uses the acquired day conversion information to obtain the parameter day information (start date, end). Get the date etc.).

(Step S309) The conversion parameter acquisition means 347 is an attribute value included in the record in which the attribute value of the translation item name matches the i-th entity from the table identified by the table identifier acquired in step S305. The converted parameters (Shain_code = 1, sta_date = 2019041, end_date = 20190430, etc.), which are the attribute values of the primary key identifier acquired in step S306, are acquired.

(Step S310) The parameter acquisition unit 34 increments the variable i. After that, the process returns to step S302.

Hereinafter, a specific operation example of the information output device according to the present embodiment will be described. The following description can be changed in various ways and does not limit the scope of the present invention.

The information output device in this example is a stand-alone terminal. For example, three table information as shown in FIG. 4 is stored in the table storage unit 11 of the information output device. FIG. 4 is a data structure diagram of table information. The table information has a table identifier and a table. An ID (for example, "1", "2", etc.) is associated with each stored table information.

For example, the table information corresponding to the ID "1" (hereinafter, may be referred to as table information 1) has a table identifier "MST_SHAIN" and a first table (employee master). In the employee master, the first item name "SHAIN_CODE" and the corresponding two or more values "1", "2" ..., And the second item name "SHAIN_CODE" and the corresponding two or more values " "Ichiro Nakamura", "Jiro Otsuka", etc. are registered.

Further, the table information 2 corresponding to the ID "2" has a table identifier "MST_GYOUMU" and a second table (business master). In the business master, the first item name "GYOUMU_ID" and the corresponding two or more values "a", "b" ..., And the second item name "GYOUMU_NAME" and the corresponding two or more values " "A project", "B project", etc. are registered.

Further, the table information 3 has a table identifier "TRN_TIME_CARD" and a third table (working time table). In the working hours table, the first item name "TRN_TIME_CARD" and the corresponding two or more values "4/1", "4/1" ... "4/2", "4/2" ... "4/30", "4/30" ..., the second item name "SHAIN_CODE" and the corresponding two or more values "1", "2" ... "1", "2" ... -"1", "2", the third item name "ZIKANGAI_TIME" and the corresponding two or more values "2", "1" ... "1", "0" ... "3", " 2 ”, the fourth item name“ TOTAL_TIME ”and the corresponding two or more values“ 10 ”,“ 9 ”・・・“ 9 ”,“ 8 ”・・・“ 11 ”,“ 10 ”, and the fifth The item name "GYOUMU_ID" and the corresponding two or more values "a", "b" ... "a", "b" ... "b", "b", etc. are registered.

For example, two or more intents as shown in FIG. 5 are stored in the intent storage unit 12. FIG. 5 is a data structure diagram of the intent. The intent has an intent name and an action name. An ID (for example, "1", "2", etc.) is associated with each stored intent.

For example, the intent 1 corresponding to the ID "1" has an intent name "overtime inquiry intent" and an action name "overtime hour inquiry". In addition, the intent 2 has an intent name “work inquiry data inquiry intent” and an action name “work inquiry data inquiry”.

The API information storage unit 13 stores, for example, a set of pairs of action names and API information as shown in FIG. FIG. 6 is a diagram showing an example of the contents of the API information storage unit 13. The pair of action name and API information is, for example, the pair of action name "overtime hours inquiry" and API information "search_overtime hours (employee code, start date, end date)", and the action name "working hours data inquiry". And the API information "service_working hours (employee code, business date, business ID)".

For example, as shown in FIG. 7, the corpus storage unit 14 stores one or more conversational sentence information in association with each of one or more intents, and further, each one or more conversational sentence information is stored. One or more entity information is also stored in association with each other. FIG. 7 is a diagram showing an example of the contents of the corpus storage unit 14. The entity information has an entity, a start position, an end position, and an entity name.

For example, the first intent "Overtime time inquiry intent" is associated with five conversational sentence information 1-5. Of these, conversational text information 1 is "tell me the overtime hours of Nakamura last month", conversational text information 2 is "tell me the overtime hours of Nakamura last month", and conversational text information 3 is "tell me the overtime hours of Nakamura last month". "Tell me the overtime hours of Nakamura", the conversational sentence information 4 is "tell me the overtime hours of last month", and the conversational sentence information 5 is "tell me the overtime hours".

The conversation text information 1 corresponding to the "overtime hour inquiry intent" includes the first entity information having the entity "Nakamura", the start position "1", the end position "2", and the entity name "employee entity". , Entity "last month", start position "4", end position "5", and second entity information with entity name "date entity", entity "overtime", start position "7", end position "10" , And a third entity information with the entity name “overtime entity”.

Further, the conversation text information 2 includes a fourth entity information having an entity "last month", a start position "1", an end position "2", and an entity name "date entity", and an entity "Nakamura", a start position ". Fifth entity information with 4 ”, end position“ 5 ”, and entity name“ employee entity ”, entity“ overtime hours ”, start position“ 7 ”, end position“ 10 ”, and entity name“ overtime entity ” Corresponds to the sixth entity information having.

Further, the conversation text information 3 includes a seventh entity information having an entity "Nakamura", a start position "1", an end position "2", and an entity name "employee entity", and an entity "overtime hours" and a start position. The eighth entity information having "4", the end position "7", and the entity name "overtime entity" is associated with each other.

Further, the conversation text information 4 includes a ninth entity information having an entity "last month", a start position "1", an end position "2", and an entity name "date entity", and an entity "overtime hours" and a start position. The tenth entity information having "4", the end position "7", and the entity name "overtime entity" is associated with each other.

Further, the conversation text information 5 is associated with eleventh entity information having an entity "overtime hours", a start position "1", an end position "4", and an entity name "overtime entity".

On the other hand, the second intent "working time data inquiry intent" is associated with, for example, 15 conversational sentence information 1 to 15. Of these, conversation sentence 1 is "Tell me the working hours of Ichiro Nakamura's A project yesterday", and conversation sentence 2 is "Tell me the working hours of Ichiro Nakamura's A project yesterday", and the last Conversational sentence 15 is "Tell me the working hours". In addition, the conversation sentence 2 and the following are sentences in which the word order is changed or some words are omitted from the conversation sentence 1.

The conversation text information 1 corresponding to the "working time data inquiry intent" is the first entity having the entity "Ichiro Nakamura", the start position "1", the end position "4", and the entity name "employee entity". Second entity information with information and entity "yesterday", start position "6", end position "7", and entity name "date entity", entity "working hours", start position "13", end position Corresponds to "16" and a third entity information having the entity name "working time entity". It should be noted that each of the conversation sentences 2 to 15 is associated with one or more entity information similarly configured.

In the entity storage unit 15, for example, as shown in FIG. 8, one or two or more entities are stored in association with each one or more entity names. FIG. 8 is a diagram showing an example of one or more entities (hereinafter, may be referred to as an entity group) corresponding to each entity name.

For example, the entity group corresponding to the entity name "employee entity" includes "Ichiro Nakamura", "Jiro Otsuka" and the like. The entity group corresponding to the entity name "date entity" includes "last month", "yesterday" and the like. The entity group corresponding to the entity name "overtime entity" includes "overtime hours", "overtime" and the like. The entity group corresponding to the entity name "business entity" includes "A matter", "B matter" and the like. The entity group corresponding to the entity name "working time entity" includes "working time", "working" and the like.

The entity mapping information storage unit 16 stores, for example, two or more entity mapping information (entity mapping information 1 to 4, etc.) as shown in FIG. FIG. 9 is a data structure diagram of entity mapping information. The entity mapping information has a table identifier, a translation item name, and an entity name.

Note that entity mapping information 1 to 3 will not be repeated as described above. The entity mapping information 4 has a table identifier "MST_GYOUMU", a translation item name "GYOUMU_ID", and an entity name "business entity".

For example, two or more PK items (PK items 1 to 4, etc.) are stored in the PK item storage unit 17, as shown in FIG. FIG. 10 is a data structure diagram of PK items. The PK item has a table identifier and a primary key identifier. Since PK items 1 to 4 have been described above, they will not be repeated.

The day conversion information storage unit 18 stores a set (not shown) of pairs of day words and day information acquisition information. The pair of the day word and the day information acquisition information is, for example, a pair of the day word "last month" and the day information acquisition information 1, a pair of the day word "yesterday" and the day information acquisition information 2, and the like. For example, the day information acquisition information 1 corresponding to the day word "last month" acquires the current time information, acquires the previous month with respect to the month held by the current time information, and refers to the calendar information of the previous month. Then, it is a program to acquire the day information from the first day to the last day of the previous month. The day information acquisition information 2 corresponding to the day word "yesterday" is a method of acquiring the current time information and acquiring the day information of the day before the day held by the current time information.

The current time is 11:15 on May 10, 2019. Now, suppose that the user voice-inputs "Tell me about Otsuka's overtime hours last month" to the terminal.

In the information output device, the voice receiving means 211 receives the above voice via the microphone, and the voice recognition means 212 performs voice recognition processing on the voice and sends a conversation sentence "Tell me about Otsuka's overtime hours last month". get.

The intent determination unit 31 determines the intent corresponding to the conversation sentence from the two or

more intents

1, 2, ... Stored in the intent storage unit 12. Specifically, the intent determination unit 31 acquires three independent words "Otsuka", "last month" and "overtime hours" from the conversation sentence by, for example, morphological analysis, and uses each independent word as a key to store the intent. 12 is searched to determine an intent 1 having an action name “overtime hours reference” that partially matches “overtime hours”.

The conversation sentence information determination unit 32 refers to the corpus storage unit 14 (FIG. 7), and has a conversation that most closely resembles the conversation sentence from among the five conversation sentence information 1 to 5 corresponding to the determined intent 1. Determine sentence information. Here, the conversation sentence information 1 is determined, in which only the employee entity "Nakamura" specified by the start position "1" and the end position "2" is different from the conversation sentence, and the other entities are the same. Employee.

The entity acquisition unit 33 is an entity corresponding to the three entities "Nakamura", "last month", and "overtime hours" corresponding to the determined conversation sentence information 1, and is the three entities possessed by the conversation sentence. A certain "Otsuka", "last month", and "overtime hours" are acquired from the entity storage unit 15.

Specifically, the conversation sentence information determination unit 32 refers to the first entity information among the first to third entity information corresponding to the conversation sentence information 1, and starts the start position “1” in the conversation sentence. And it is determined that "Otsuka" specified by the end position "2" is an employee entity. Next, the conversation sentence information determination unit 32 refers to the entity storage unit 15 and acquires the entity "Otsuka Jiro" that partially matches "Otsuka" from the entity group corresponding to the entity name "employee entity".

Further, the conversation sentence information determination unit 32 refers to the second entity information and determines that the "last month" specified by the start position "4" and the end position "5" in the conversation sentence is the date entity. , Get the entity "last month" that exactly matches "last month" from the entity group corresponding to the entity name "date entity".

Further, the conversation sentence information determination unit 32 determines that the “overtime hours” specified by the start position “7” and the end position “10” in the conversation sentence is the overtime entity by referring to the third entity information. Then, from the entity group corresponding to the entity name "overtime entity", the entity "overtime hours" that exactly matches the "overtime hours" is acquired.

In this way, when the three entities "Jiro Otsuka", "last month", and "overtime hours" corresponding to the conversation sentence are acquired, the parameter acquisition unit 34 acquires the three parameters corresponding to the three entities. ..

Specifically, first, regarding the first entity "Jiro Otsuka", the entity name acquisition means 343 constituting the parameter acquisition unit 34 uses the first entity information to transfer the entity name "employee entity" from the entity storage unit 15. get. Next, the translation item name acquisition means 344 acquires the translation item name “SHAIN_NAME” paired with the acquired entity name “employee entity” from the entity mapping information storage unit 16 using the entity mapping information 1. Further, the table identifier acquisition means 345 acquires the table identifier "MST_SHAIN" paired with the acquired entity name "employee entity" from the entity mapping information storage unit 16 using the entity mapping information 1.

Next, the primary key identifier acquisition means 346 acquires the primary key identifier "SHAIN_CODE" paired with the acquired table identifier "MST_SHAIN" from the PK item storage unit 17 using the PK item 1. Further, the determination means 341 determines that the first entity "Otsuka" is not a Japanese word, and the conversion parameter acquisition means 347 corresponds to the table (employee master) identified by the acquired table identifier "MST_SHAIN". Therefore, the attribute value of the translation item name "SHAIN_NAME" is the attribute value included in the record matching the first entity "Jiro Otsuka", and is the attribute value of the acquired primary key identifier "SHAIN_CODE". Acquires the converted parameter "shain_code = 2" of the eye.

Next, regarding the second entity "last month", the entity name acquisition means 343 acquires the entity name "date entity" corresponding to the "last month", and the translation item name acquisition means 344 acquires the acquired entity name "date". The translation item name "TIME_CARD_DATE" paired with "entity" is acquired by using the entity mapping information 2. The table identifier acquisition means 345 acquires the table identifier “TRN_TIME_CARD” paired with the acquired entity name “date entity” from the entity mapping information storage unit 16 using the entity mapping information 2.

Next, the primary key identifier acquisition means 346 acquires two primary key identifiers "SHAIN_CODE" and "TIME_CARD_DATE" that are paired with the acquired table identifier "TRN_TIME_CARD" using the two

PK items

2 and 3. The determination means 341 determines that the second entity "last month" is a day word, and in response to this, the day information acquisition means 342 stores the day conversion information corresponding to the day word "last month". The day information "4/1 to 4/30" is acquired by using the acquired day conversion information acquired from the unit 18.

Specifically, the day information acquisition means 342 acquires the current time information "May 10, 2019 11:15" from the built-in clock or the like, and April, which is the month before "May" in the current time information. With reference to the calendar information of, the day information "4/1 to 4/30" indicating 30 days from the start date "4/1" to the end date "4/30" is acquired.

The conversion parameter acquisition means 347 has a start date in which the attribute value of the translation item name "TIME_CARD_DATE" corresponds to the second entity "last month" from the table (working time table) identified by the acquired table identifier "TRN_TIME_CARD". The second and the attribute values included in the records that match "4/1" and the end date "4/30", which are the attribute values of the two acquired primary key identifiers "SHAIN_CODE" and "TIME_CARD_DATE". The third converted parameters "sta_date = 2019041" and "end_date = 20190430" are acquired.

Next, regarding the third entity "overtime hours", the entity name acquisition means 343 acquires the entity name "overtime entity" corresponding to the "overtime hours", and the translation item name acquisition means 344 acquires the acquired entity name. The translation item name "ZIKANGAI_TIME" paired with "overtime entity" is acquired by using the entity mapping information 3. Further, the table identifier acquisition means 345 acquires the table identifier "TRN_TIME_CARD" paired with the acquired entity name "overtime entity" by using the entity mapping information 3.

Since the two primary key identifiers "SHAIN_CODE" and "TIME_CARD_DATE" paired with the acquired table identifier "TRN_TIME_CARD" have already been acquired, the primary key identifier acquisition means 346 normally does not acquire them. You may get it again.

Further, the determination means 341 determines that the third entity "overtime hours" is not a day word, and the conversion parameter acquisition means 347 has a translation item name of the working hours table identified by the acquired table identifier "TRN_TIME_CARD". Acquire the fourth converted parameter "zikangai_time" corresponding to "ZIKANGAI_TIME".

In this way, when the four parameters "shain_code = 2", "sta_date = 2019041", "end_date = 20190430" and "zikangai_time" corresponding to the conversation sentence "Tell me about the overtime hours of Otsuka last month" are acquired, the API The information acquisition unit 35 acquires the API information “sent_overtime hours (employee code, start date, end date)” corresponding to the action name “overtime time inquiry” possessed by the determined intent 1 from the API information storage unit 13. ..

The inquiry information configuration unit 36 substitutes the acquired four parameters into the corresponding variables of the acquired API information "search_overtime hours (employee code, start date, end date)" to obtain inquiry information. It constitutes "service_zikangai_time (shain_code = 2, sta_date = 2019041, end_date = 20190430".

The search unit 37 executes the configured inquiry information and acquires the search result. Here, from the overtime hours table identified by the table identifier "TRN_TIME_CARD", the value of the item name "TIME_CARD_DATE" is "4/1" to "4/30", and the value of SHAIN_CODE is "2" 30. From the records, 30 values "1,0, ... 2" corresponding to the item name "ZIKANGAI_TIME" are acquired, and the search result "20 hours" which is the sum of the 30 values is acquired.

The search result output unit 41 outputs a response sentence including the acquired search result "20 hours". The output response text may be, for example, "20 hours" or "Otsuka-sama's overtime hours in April is 20 hours". Specifically, for example, the template of the response sentence is stored in the storage unit 1, and the search result output unit 41 sets the variable of the template to the above search result "20 hours" and "obtained from the conversation sentence". The response sentence may be constructed by substituting "Otsuka" and "April" obtained in the search process.

Although detailed explanation is omitted, for the conversational sentence "Tell me yesterday's working hours of A project of Jiro Otsuka", for example, four parameters "shain_code = 2", "time_card_date = 20190509", " "Gyoumu_id = a" and "total_time" may be acquired, and the inquiry information "sent_total_time (sent_code = 2, time_card_date = 20109009, gyoumu_id = a" may be configured.

(Modification example 1)
When the API information is the SQL statement "select_overtime_from_table name_where_employee code, business date", the parameter acquisition unit 34 has four parameters "shain_code = 2", "time_caed_date = 20190509", "trn_time_card", And "zikangai_time" may be acquired, and the inquiry information configuration unit 36 may configure the inquiry information "select_zikangai_time_from_trans_time_card_where_shain_code = 2, time_caed_date = 20190509".

(Modification 2)
When the API information is a set of URL and method "http://develop.soppra ...? Employee code & start date & end date", the parameter acquisition unit 34 has four parameters "shain_code = 2", Acquiring "sta_date = 20190401", "end_date = 20190430", and "zikangai_time", the inquiry information component 36 receives the inquiry information "http://develop.soppra ...? Shan_code = 2 & start_date = 2019041 & May be configured.

As described above, according to the present embodiment, one or more intents, which are information managed for each business process and have an action name for specifying the business process, are stored in the intent storage unit 12, and the API is The information storage unit 13 stores one or more API information, which is information corresponding to the intent, information for performing an information search, and information having information for specifying a parameter which is one or more variables. The corpus storage unit 14 stores one or more conversational sentence information which is information corresponding to the intent and is conversational sentence information, and the entity storage unit 15 corresponds to any one or more conversational sentence information. One or more entities that are words are stored, and the information output device receives the conversation sentence, determines the intent corresponding to the received conversation sentence, and from the one or more conversation sentence information corresponding to the determined intent. , Determines the conversational sentence information that most closely resembles the received conversational sentence, corresponds to one or more entities corresponding to the determined conversational sentence information, and acquires one or more entities that are words of the received conversational sentence. Then, one or more parameters corresponding to one or more acquired entities are acquired, API information corresponding to the determined intent is acquired from the API information storage unit 13, and the acquired one or more parameters and the acquired API are acquired. Even in a query that asks for the same search result by constructing inquiry information for information search using information, executing the configured inquiry information, acquiring search results, and outputting the acquired search results. It is possible to accept dynamically changing conversational sentences and search for information.

Further, the information output device acquires the text corresponding to the received conversational sentence, acquires one or more independent words from the text, and creates an intent having an action name having a word that is the same as or similar to one or more independent words. By making a decision, it is possible to accept dynamically changing conversational sentences and search for information even with a query requesting the same search result.

Further, in the day conversion information storage unit 18, the day word which is a word related to the day and the day information which is the information about the day corresponding to the day word and which is the information used when constructing the inquiry information is acquired. One or more day conversion information having the day information acquisition information is stored, and the information output device acquires the day conversion information corresponding to the day word in the acquired one or more entities from the day conversion information storage unit 18. By acquiring the parameter day information using the day conversion information, it is possible to accept dynamically changing conversational sentences even in a query for the same search result, and to appropriately search for information.

In the above configuration, the information output device determines whether or not the day word exists in the acquired one or more entities, and if it determines that the day word exists, the day conversion information corresponding to the day word. May be acquired from the day conversion information storage unit 18, and the day information which is a parameter may be acquired by using the day conversion information. As a result, it is possible to accept dynamically changing conversational sentences even in a query for the same search result regardless of the presence or absence of a Japanese word, and to appropriately search for information.

Further, the entity of the entity storage unit 15 corresponds to the entity name which is the name of the entity, and the entity mapping information storage unit 16 has a table identifier for specifying the table and an attribute name in the table identified by the table identifier. A table in which one or more entity mapping information having a translation item name and an entity name, which is information for identifying the entity to be converted, is stored, and is identified by a table identifier and a table identifier in the PK item storage unit 17. One or more PK items having a primary key identifier that identifies the primary key of are stored, and the information output device acquires the entity name corresponding to the acquired entity and obtains the translation item name paired with the acquired entity name. The table identifier that is acquired from the entity mapping information storage unit 16 and is paired with the acquired entity name is acquired from the entity mapping information storage unit 16, and the primary key identifier that is paired with the acquired table identifier is acquired from the PK item storage unit 17. Then, from the table identified by the acquired table identifier, the attribute value of the acquired translation item name is the attribute value included in the record that matches the acquired entity, and is the attribute value of the acquired primary key identifier. By acquiring the parameters, it is possible to accept dynamically changing conversational sentences even with a query for the same search result, and to search for information appropriately.

Further, the information output device is a parameter corresponding to each place in each place of one or more variables possessed by the acquired API information, and the same search result is obtained by arranging the acquired parameters and constructing the inquiry information. It is possible to search for information by accepting dynamically changing conversational sentences even when inquiring about.

In addition, the information output device receives the voice of the conversational sentence, performs voice recognition processing on the voice, and acquires the conversational sentence which is a character string, so that even a query for the same search result can be dynamically changed by the voice. You can accept conversational sentences and search for information.

Further, the processing in the present embodiment may be realized by software. Then, this software may be distributed by software download or the like. Further, this software may be recorded on a recording medium such as a CD-ROM and disseminated. It should be noted that this also applies to other embodiments herein.

The software that realizes the information output device in this embodiment is, for example, the following program. That is, this program corresponds to the intent storage unit 12 and the intent that store one or more intents that are information managed for each business process and have an action name that specifies the business process. Corresponds to the API information storage unit 13 and the intent in which one or more API information is stored, which is information that exists, is information for performing an information search, and is information that has information that specifies a parameter that is one or more variables. A corpus storage unit 14 that stores one or more conversational sentence information that is attached information and is conversational sentence information, and an entity that stores one or more entities that are words corresponding to any one or more conversational sentence information. The computer that can access the storage unit 15 has a conversation sentence reception unit 21 that accepts conversation sentences, an intent determination unit 31 that determines an intent corresponding to the conversation sentence received by the conversation sentence reception unit 21, and the intent. From one or more conversational sentence information corresponding to the intent determined by the determination unit 31, the conversational sentence information determination unit 32 that determines the conversational sentence information most similar to the conversational sentence received by the conversational sentence reception unit 21 Acquires one or more entities that correspond to one or more entities corresponding to the conversational sentence information determined by the conversational sentence information determination unit 32 and are words possessed by the conversational sentence received by the conversational sentence reception unit 21. The entity acquisition unit 33, the parameter acquisition unit 34 that acquires one or more parameters corresponding to one or more entities acquired by the entity acquisition unit 33, and the API corresponding to the intent determined by the intent determination unit 31. Information search using the API information acquisition unit 35 that acquires information from the API information storage unit 13, one or more parameters acquired by the parameter acquisition unit 34, and the API information acquired by the API information acquisition unit 35. The inquiry information configuration unit 36 that constitutes the inquiry information for the purpose, the search unit 37 that executes the inquiry information configured by the inquiry information configuration unit 36 and acquires the search result, and the search unit 37 acquire the information. This is a program for functioning as a search result output unit 41 that outputs the searched result.

FIG. 11 is an external view of a computer system 900 that executes a program according to the present embodiment to realize an information output device. This embodiment can be realized by computer hardware and a computer program executed on the computer hardware. In FIG. 11, the computer system 900 includes a computer 901 including a disk drive 905, a keyboard 902, a mouse 903, a display 904, a microphone 917, and a speaker 918. The entire system including the keyboard 902, the mouse 903, the display 904, the microphone 917, and the speaker 918 may be called a computer.

FIG. 12 is a diagram showing an example of the internal configuration of the computer system 900. In FIG. 12, the computer 901 is connected to the MPU 911, the ROM 912 for storing a program such as a boot-up program, and the MPU 911 in addition to the disk drive 905, and temporarily stores the instructions of the application program and temporarily. It provides a RAM 913 that provides a storage space, a storage 914 that stores application programs, system programs, and data, a bus 915 that interconnects the MPU 911, ROM 912, and the like, and a connection to a network such as an external network or an internal network. It includes a network card 916. The storage 914 is, for example, a hard disk, an SSD, a flash memory, or the like.

A program for causing the computer system 900 to execute the function of the information output device may be stored in a disk 921 such as a DVD or a CD-ROM, inserted into the disk drive 905, and transferred to the storage 914. Alternatively, the program may be transmitted to computer 901 over the network and stored in storage 914. The program is loaded into RAM 913 at run time. The program may be loaded directly from disk 921 or the network. Further, the program may be read into the computer system 900 via another removable recording medium (for example, a DVD, a memory card, etc.) instead of the disk 921.

The program does not necessarily include an operating system (OS) for executing the function of the information output device, a third-party program, or the like in 901 showing the details of the computer. The program may contain only a portion of instructions that call the appropriate function or module in a controlled manner to achieve the desired result. It is well known how the computer system 900 works, and detailed description thereof will be omitted.

The computer system 900 described above is a server or a stationary PC, but the information output device may be realized by a mobile terminal such as a tablet terminal, a smartphone, or a notebook PC. In this case, for example, the keyboard 902 and the mouse 903 may be replaced with a touch panel, the disk drive 905 may be replaced with a memory card slot, and the disk 921 may be replaced with a memory card. However, the above is an example, and the hardware configuration of the computer that realizes the information output device does not matter.

In the above program, in the transmission step of transmitting information and the receiving step of receiving information, processing performed by hardware, for example, processing performed by a modem or interface card in the transmission step (only performed by hardware). Processing that is not done) is not included.

Further, the number of computers that execute the above program may be singular or plural. That is, centralized processing may be performed, or distributed processing may be performed.

Further, in each of the above embodiments, even if the two or more communication means existing in one device (for example, the reception function of the reception unit 2 and the transmission function of the output unit 4) are physically realized by one medium. Needless to say, it's good.

Further, in each of the above-described embodiments, each process (each function) may be realized by centralized processing by a single device (system), or by distributed processing by a plurality of devices. May be done.

It goes without saying that the present invention is not limited to the above embodiments, and various modifications can be made, and these are also included in the scope of the present invention.

As described above, the information output device according to the present invention has the effect of being able to accept dynamically changing conversational sentences and search for information even with an inquiry for the same search result, and is useful as an information output device or the like. is there.

Claims

An intent storage unit that stores one or more intents that are information managed for each business process and have an action name that identifies the business process.
An API information storage unit that stores one or more API information that is information associated with an intent, information for information retrieval, and information that has information for specifying a parameter that is one or more variables. When,
A corpus storage unit that stores one or more conversational sentence information that is information corresponding to the intent and is conversational sentence information.
An entity storage unit that stores one or more entities that are words corresponding to any one or more conversational sentence information, and
Conversational sentence reception department that accepts conversational sentences and
The intent determination unit that determines the intent corresponding to the conversation sentence received by the conversation sentence reception unit, and the intent determination unit.
From one or more conversational sentence information corresponding to the intent determined by the intent determination unit, the conversational sentence information determination unit that determines the conversational sentence information most similar to the conversational sentence received by the conversational sentence reception unit, and
Entity acquisition that corresponds to each one or more entities corresponding to the conversational sentence information determined by the conversational sentence information determination unit, and acquires one or more entities that are words of the conversational sentence received by the conversational sentence reception unit. Department and
A parameter acquisition unit that acquires one or more parameters corresponding to one or more entities acquired by the entity acquisition unit, and a parameter acquisition unit.
An API information acquisition unit that acquires API information corresponding to the intent determined by the intent determination unit from the API information storage unit, and
An inquiry information configuration unit that configures inquiry information for information retrieval using one or more parameters acquired by the parameter acquisition unit and API information acquired by the API information acquisition unit.
A search unit that executes inquiry information configured by the inquiry information configuration unit and acquires search results,
An information output device including a search result output unit that outputs a search result acquired by the search unit.
The intent determination unit
An intent having an action name that acquires a text corresponding to a conversation sentence received by the conversation sentence reception unit, acquires one or more independent words from the text, and has a word that is the same as or similar to the one or more independent words. The information output device according to claim 1.
One or more having a day word which is a word related to a day and a day information acquisition information for acquiring day information which is information about a day corresponding to the day word and is information used when constructing inquiry information. It also has a day conversion information storage unit that stores the day conversion information of
The parameter acquisition unit
A claim for acquiring day conversion information corresponding to a day word in one or more entities acquired by the entity acquisition unit from the day conversion information storage unit, and using the day conversion information to acquire parameter day information. The information output device according to claim 1 or 2.
The entity in the entity storage unit corresponds to the entity name which is the name of the entity.
One or more entity mapping information having a table identifier that identifies a table, a translation item name that is an attribute name in the table identified by the table identifier and is information that identifies the entity to be converted, and an entity name. The stored entity mapping information storage unit and
It further includes a PK item storage unit for storing one or more PK items having a table identifier and a primary key identifier that identifies the primary key of the table identified by the table identifier.
The parameter acquisition unit
An entity name acquisition means for acquiring an entity name corresponding to an entity acquired by the entity acquisition unit, and
A translation item name acquisition means for acquiring a translation item name paired with an entity name acquired by the entity name acquisition means from the entity mapping information storage unit, and a translation item name acquisition means.
A table identifier acquisition means for acquiring a table identifier paired with an entity name acquired by the entity name acquisition means from the entity mapping information storage unit, and a table identifier acquisition means.
A primary key identifier acquisition means that acquires a primary key identifier paired with a table identifier acquired by the table identifier acquisition means from the PK item storage unit, and
From the table identified by the table identifier acquired by the table identifier acquisition means, the attribute value of the translation item name acquired by the translation item name acquisition means is included in the record matching the entity acquired by the entity acquisition unit. The item according to any one of claims 1 to 3, further comprising a conversion parameter acquisition means for acquiring a converted parameter which is a value and is an attribute value of the primary key identifier acquired by the primary key identifier acquisition means. Information output device.
The inquiry information component unit
Claims that are parameters corresponding to each of the one or more variables possessed by the API information acquired by the API information acquisition unit, and the parameters acquired by the parameter acquisition unit are arranged to form inquiry information. The information output device according to any one of items 1 to 4.
The reception department
A voice reception means that accepts the voice of conversational sentences,
The information output device according to any one of claims 1 to 5, further comprising a voice recognition means for performing voice recognition processing on the voice and acquiring a conversational sentence which is a character string.
Information that is managed for each business process, and is information that has an action name that identifies the business process. It is an intent storage unit that stores one or more intents, and information that corresponds to the intent. The information corresponding to the API information storage unit and the intent that stores one or more API information, which is the information that has the information to specify the parameter that is one or more variables, and is the information of the conversational sentence. A corpus storage unit that stores one or more conversational sentence information that is information, an entity storage unit that stores one or more entities that are words corresponding to any one or more conversational sentence information, a conversational sentence reception unit, and an intent. It is an information output method realized by a determination unit, a conversational sentence information determination unit, an entity acquisition unit, a parameter acquisition unit, an API information acquisition unit, an inquiry information composition unit, a search unit, and a search result output unit.
The conversation sentence reception step in which the conversation sentence reception section accepts the conversation sentence, and
An intent determination step in which the intent determination unit determines an intent corresponding to the conversation sentence received by the conversation sentence reception unit, and
The conversation sentence information determination unit determines the conversation sentence information most similar to the conversation sentence received by the conversation sentence reception unit from one or more conversation sentence information corresponding to the intent determined by the intent determination unit. Conversational sentence information determination step and
The entity acquisition unit corresponds to one or more entities corresponding to the conversation sentence information determined by the conversation sentence information determination unit, and one or more words possessed by the conversation sentence received by the conversation sentence reception unit. The entity acquisition step to acquire the entity and
A parameter acquisition step in which the parameter acquisition unit acquires one or more parameters corresponding to one or more entities acquired by the entity acquisition unit.
An API information acquisition step in which the API information acquisition unit acquires API information corresponding to the intent determined by the intent determination unit from the API information storage unit.
Inquiry information that constitutes inquiry information for information retrieval by the inquiry information composition unit using one or more parameters acquired by the parameter acquisition unit and API information acquired by the API information acquisition unit. Configuration steps and
A search step in which the search unit executes the inquiry information configured by the inquiry information configuration unit and acquires a search result.
An information output method including a search result output step in which the output unit outputs a search result acquired by the search unit.
Information that is managed for each business process, and is information that has an action name that identifies the business process. It is an intent storage unit that stores one or more intents, and information that corresponds to the intent. The information corresponding to the API information storage unit and the intent that stores one or more API information, which is the information that has the information to specify the parameter that is one or more variables, and is the information of the conversational sentence. A computer that can access a corpus storage unit that stores one or more conversational sentence information that is information, and an entity storage unit that stores one or more entities that are words corresponding to any one or more conversational sentence information.
Conversational sentence reception department that accepts conversational sentences and
The intent determination unit that determines the intent corresponding to the conversation sentence received by the conversation sentence reception unit, and the intent determination unit.
From one or more conversational sentence information corresponding to the intent determined by the intent determination unit, the conversational sentence information determination unit that determines the conversational sentence information most similar to the conversational sentence received by the conversational sentence reception unit, and
Entity acquisition that corresponds to each one or more entities corresponding to the conversational sentence information determined by the conversational sentence information determination unit, and acquires one or more entities that are words of the conversational sentence received by the conversational sentence reception unit. Department and
A parameter acquisition unit that acquires one or more parameters corresponding to one or more entities acquired by the entity acquisition unit, and a parameter acquisition unit.
An API information acquisition unit that acquires API information corresponding to the intent determined by the intent determination unit from the API information storage unit, and
An inquiry information configuration unit that configures inquiry information for information retrieval using one or more parameters acquired by the parameter acquisition unit and API information acquired by the API information acquisition unit.
A search unit that executes inquiry information configured by the inquiry information configuration unit and acquires search results,
A program for functioning as a search result output unit that outputs the search results acquired by the search unit.