Search support program, search support method, and information processing device.

Abstract

To assist students in searching for their desired schools. [Solution] When the information processing device receives conversation data 815 in response to output conversation data 814, it refers to the target school search condition table and determines whether the content of the statement shown in the received conversation data 815 contains any of the keywords corresponding to the question shown in the output conversation data 814 for each item used to classify the schools to be searched. For example, suppose that for the item "Faculty," the content of the statement shown in conversation data 811 contains the keyword "Education" corresponding to the question shown in conversation data 814. In this case, the information processing device 101 sets the condition "Education" corresponding to the question shown in conversation data 814 and the keyword "Education" for the item "Faculty," as a target school narrowing condition.

Description

Technical Field

[0001] The present invention relates to a search support program, a search support method, and an information processing device.

Background Art

[0002] Conventionally, there is a system for searching for schools as desired schools. For example, in college entrance examinations, when searching for a university as a desired school, a user can search for the desired school based on the set search conditions by setting search conditions such as faculties and departments of interest.

[0003] As a prior art, for example, there is a system in which a student registers a student tag in a school-student search system using a student terminal device, and a school registers a school tag in the school-student search system using a school terminal device. In the school-student search system, a student searches for schools based on school tags using a student terminal device, and a school searches for students based on student tags using a school terminal device.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, in the prior art, when searching for a school as a desired school, a user cannot determine what search conditions should be set, and it may be difficult to search for a desired school suitable for the user.

[0006] In one aspect, an object of the present invention is to provide a search support program, a search support method, and an information processing device for supporting the search for desired schools.

Means for Solving the Problems

[0007] To solve the above-mentioned problems and achieve the objective, the search support program according to this invention is characterized in that, in a conversation with a user regarding the selection of a desired school, it outputs first conversation data indicating questions to the user, and when it receives second conversation data indicating the content of the user's statements in response to the output first conversation data, it refers to a storage unit that stores conditions that can be used to search for schools and keywords related to the selection of the desired school in association with each of those conditions, determines whether any of the keywords stored in the storage unit are included in the content of the statements indicated in the second conversation data, and if it determines that any of the keywords are included, it sets the conditions stored in the storage unit in association with the keyword as search conditions for searching for candidate schools for the desired school, and causes the computer to execute the following process.

[0008] Furthermore, the search support program according to the present invention is characterized in that, in the above invention, the computer repeatedly performs the output process, the judgment process, and the setting process while switching the questions to the user based on the second conversation data received.

[0009] Furthermore, the search support program according to this invention is characterized in that, upon receiving a search instruction for the desired school, it causes the computer to perform a process that outputs search results indicating candidate schools for the desired school, based on the conditions set in the search criteria.

[0010] Furthermore, the search support program according to this invention is characterized in that, upon receiving a search instruction for the desired school, it causes the computer to perform a process that outputs search results indicating candidate schools for the desired school, based on the conditions set in the search criteria and the user's academic test results.

[0011] Furthermore, the search support program according to this invention is characterized in that, in the above invention, the storage unit stores, for each condition that can be used to search for schools to be searched, the conditions and the questions and keywords related to the selection of the desired school in association with each condition, the determination process refers to the storage unit to determine whether the content of the statement shown in the second conversation data contains any of the keywords corresponding to the questions shown in the first conversation data, and the setting process, if it determines that any of the keywords are included, sets conditions in the search conditions that correspond to the questions shown in the first conversation data and any of the keywords.

[0012] Furthermore, the search support program according to the present invention is characterized in that, in the above invention, the memory unit stores, for each of the multiple items for classifying schools to be searched, a condition that can be used to search for schools and a keyword related to the selection of the desired school in association with that condition, and the judgment process refers to the memory unit to determine, for each of the items, whether the content of the statement indicated by the received second conversation data contains any of the keywords stored in the memory unit, and if the setting process determines that any of the keywords are included for each of the items, it sets the condition stored in the memory unit in association with that keyword in the search conditions.

[0013] Furthermore, the search support method according to this invention is characterized in that, in a conversation with a user regarding the selection of a desired school, the computer outputs first conversation data indicating questions to the user, and when it receives second conversation data indicating the content of the user's statements in response to the output first conversation data, it refers to a storage unit that stores conditions that can be used to search for schools and associates those conditions with keywords related to the selection of the desired school, and determines whether any of the keywords stored in the storage unit are included in the content of the statements indicated in the second conversation data, and if it is determined that any of the keywords are included, it sets the conditions stored in the storage unit in association with those keywords as search conditions for searching for candidate schools for the desired school.

[0014] Furthermore, the information processing device according to this invention is characterized in that, in a conversation with a user regarding the selection of a desired school, it outputs first conversation data indicating a question to the user, and when it receives second conversation data indicating the content of the user's response to the output first conversation data, it refers to a storage unit that stores, for each condition usable for searching for schools to be searched, a condition associated with the selection of the desired school, and determines whether or not any of the keywords stored in the storage unit are included in the content of the second conversation data, and if it determines that any of the keywords are included, it sets the condition stored in the storage unit associated with any of the keywords as a search condition for searching for candidate schools for the desired school. [Effects of the Invention]

[0015] The search support program, search support method, and information processing device according to this invention have the effect of supporting the search for desired schools. [Brief explanation of the drawing]

[0016] [Figure 1] Figure 1 is an explanatory diagram showing an example of the system configuration of the school matching system 100 according to the embodiment. [Figure 2] Figure 2 is a block diagram showing an example of the hardware configuration of the information processing apparatus 101 according to the embodiment. [Figure 3] Figure 3 is a block diagram showing an example of the functional configuration of the information processing apparatus 101. [Figure 4] Figure 4 is an explanatory diagram showing an example of the stored content of the desired school search condition table 400. [Figure 5] Figure 5 is an explanatory diagram (Part 1) showing an example of the screen of the desired school consultation screen. [Figure 6] Figure 6 is an explanatory diagram (Part 2) showing an example of the screen of the desired school consultation screen. [Figure 7] Figure 7 is an explanatory diagram (Part 3) showing an example of the screen of the desired school consultation screen. [Figure 8] Figure 8 is an explanatory diagram (Part 4) showing an example of the screen of the desired school consultation screen. [Figure 9] Figure 9 is an explanatory diagram (Part 5) showing an example of the screen of the desired school consultation screen. [Figure 10] Figure 10 is an explanatory diagram (Part 6) showing an example of the screen of the desired school consultation screen. [Figure 11] Figure 11 is an explanatory diagram showing an example of the screen of the desired school setting screen. [Figure 12] Figure 12 is a sequence diagram showing an example of the operation of the desired school matching system 100. [Figure 13] Figure 13 is a flowchart showing an example of the specific processing procedure of the desired school narrowing-down condition setting process.

Embodiments for Carrying Out the Invention

[0017] Hereinafter, embodiments of the search support program, search support method, and information processing apparatus according to the present invention will be described in detail with reference to the drawings.

[0018] (Embodiment) First, a system configuration example of the desired school matching system 100 including the information processing apparatus 101 according to the embodiment will be described.

[0019] Figure 1 is an explanatory diagram showing an example of the system configuration of a school matching system 100 according to an embodiment. In Figure 1, the school matching system 100 includes a plurality of information processing devices 101 and an information providing server 102. In the school matching system 100, the information processing devices 101 and the information providing server 102 are connected via a wired or wireless network 110. The network 110 is, for example, the Internet, a LAN (Local Area Network), or a WAN (Wide Area Network).

[0020] Here, the information processing device 101 is a computer that assists in searching for prospective schools. The information processing device 101 is, for example, a PC (Personal Computer), tablet PC, or smartphone used by a user of the prospective school matching system 100.

[0021] A "desired school" is the school you aim to attend. A user is, for example, someone who hasn't yet decided on a desired school and is looking for one that suits them. In the case of junior high school entrance exams, the desired school is the junior high school the user is aiming for. In the case of high school entrance exams, the desired school is the high school the user is aiming for. In the case of university entrance exams, the desired school is the university the user is aiming for.

[0022] The following explanation uses university entrance exams as an example to describe how to assist users in searching for their desired universities. In this case, the users are, for example, high school students or students who have taken a gap year before entering university.

[0023] The information provision server 102 is a computer that has a school information master DB (Database) 120 and a function to search for school information that meets the set search conditions. The school information master DB 120 stores school information for universities. Universities include, for example, comprehensive universities, colleges of specialized fields, and junior colleges.

[0024] School information may include, for example, the university name, its phonetic spelling, its type (national, public, or private), the prefecture where its headquarters are located, the campus location (latitude and longitude information), the name of the faculty, the name of the department, the name of the course, whether it is evening or daytime classes, the entrance examination subjects, the entrance examination schedule, the minimum passing score, and a university guide. School information may also include information about the entrance examination method, whether it is a women's university or co-educational, and whether it is a distance learning or on-campus program.

[0025] The target school matching system 100 can be applied, for example, to a learning support system that proposes an optimal study plan for passing the target school's entrance exam. While the information processing device 101 and the information provision server 102 are provided separately in this example, this is not the only configuration. For instance, the information processing device 101 may be implemented by the information provision server 102.

[0026] In conventional systems, when searching for a school of interest, users had to select or enter search criteria to narrow down the options to schools that suited them. However, some users may find it difficult to determine what search criteria to set when searching for a school of interest.

[0027] For example, in the case of university entrance exams, high school freshmen and sophomores often find it difficult to concretely imagine the schools they want to attend and are unable to determine the criteria needed to narrow down the schools that are right for them. If appropriate criteria cannot be set, it is difficult to search for schools that are a good fit for the user.

[0028] Therefore, in this embodiment, we will describe a search support method that assists in searching for a desired school by automatically setting conditions for searching for a school that matches the user's preferences through dialogue with AI (Artificial Intelligence) during a conversation about selecting a desired school.

[0029] (Example of hardware configuration of information processing device 101) Next, we will describe an example of the hardware configuration of the information processing device 101.

[0030] Figure 2 is a block diagram showing an example of the hardware configuration of an information processing device 101 according to an embodiment. In Figure 2, the information processing device 101 includes a CPU (Central Processing Unit) 201, a ROM (Read Only Memory) 202, and a RAM (Random Access Memory) 203.

[0031] The information processing device 101 also includes an HDD (Hard Disc Drive) 204, an HD 205, a CD (Compact Disc)-RW (ReWritable) drive 206, and a CD-RW 207. Furthermore, the information processing device 101 includes a display 208, a keyboard 209, a mouse 210, and a network interface 211. Each component is connected by a bus 200.

[0032] Here, the CPU 201 controls the entire information processing unit 101. The CPU 201 may have multiple cores. The ROM 202 and HD 205 store various programs. The programs stored in the ROM 202 and HD 205 are, for example, this search support program. The program stored in the ROM 202 is loaded into the CPU 201, causing the CPU 201 to execute the coded process. The RAM 203 is used as the work area for the CPU 201.

[0033] HDD204 controls the reading or writing of data to HD205 according to the control of CPU201. HD205 stores the data written according to the control of HDD204. CD-RW drive 206 controls the reading or writing of data to CD-RW207 according to the control of CPU201. CD-RW207 stores the data written according to the control of CD-RW drive 206. CD-RW207 may be removable from, for example, the information processing device 101.

[0034] Display 208 displays various data such as cursors, icons, menus, windows, toolboxes, text, images, or function information. Display 208 can be, for example, an LCD display or an OLED (Electroluminescence) display.

[0035] The keyboard 209 has keys for inputting characters, numbers, and various instructions, and is used for data input. The mouse 210 is used for selecting or executing various instructions, selecting the object to be processed, or moving the mouse pointer. The display 208 may also be a touch panel and have functions equivalent to the keyboard 209 and the mouse 210. In this case, the information processing device 101 does not need to have a keyboard 209 and a mouse 210.

[0036] The network interface 211 is connected to the network 110 via a communication line, and through the network 110, it is connected to other computers (for example, the information provision server 102 shown in Figure 1). The network interface 211 manages the interface between the network 110 and the inside of the information processing device 101, and controls the input and output of data from other computers. The network interface 211 is, for example, a modem or a LAN adapter.

[0037] In addition to the components described above, the information processing device 101 may also have, for example, a DVD (Digital Versatile Disc) drive, an SSD (Solid State Drive), etc. Furthermore, the information processing device 101 may also have, for example, a USB (Universal Serial Bus) port. Furthermore, the information processing device 101 may also have, for example, a printer, scanner, microphone, speaker, etc. Moreover, the information processing device 101 may not have, for example, an HDD 204, HD 205, CD-RW drive 206, CD-RW 207, etc., among the components described above.

[0038] (Example of the functional configuration of the information processing device 101) Next, we will describe an example of the functional configuration of the information processing device 101.

[0039] Figure 3 is a block diagram showing an example of the functional configuration of the information processing device 101. In Figure 3, the information processing device 101 includes a reception unit 301, a conversation control unit 302, a setting unit 303, a search unit 304, and a storage unit 310. The reception unit 301 to the search unit 304 are control units, and their functions are realized, for example, by having the CPU 201 execute a program stored in a storage device such as the ROM 202, RAM 203, and HD 205 shown in Figure 2, or by using the network I / F 211. The processing results of each functional unit are stored in a storage device such as the RAM 203 and HD 205. The storage unit 310 is realized by a storage device such as the RAM 203 and HD 205. Specifically, for example, the storage unit 310 stores a target school search condition table 400 as shown in Figure 4, which will be described later.

[0040] The reception unit 301 receives requests to initiate a conversation regarding the selection of prospective schools. Here, a request to initiate a conversation might be, for example, a request to start a conversation with a strategic AI coach to discuss prospective schools. The strategic AI coach is software that can interact with the user using AI technology (for example, the strategic AI coach 501 shown in Figure 5 below).

[0041] The conversation with the strategic AI coach may be controlled, for example, according to a pre-created scenario. The scenario is information that outlines the flow of conversation between the strategic AI coach and the user. For example, a scenario may be created that guides the user through conversation so that useful keywords for narrowing down schools can be elicited.

[0042] Furthermore, the conversations of the strategic AI coach may be implemented using language models such as LLMs (Large Language Models). For example, the conversations of the strategic AI coach may be generated by giving a language model prompts that instruct it to generate conversations that extract useful vocabulary for narrowing down schools.

[0043] Specifically, for example, the reception unit 301 receives an instruction to start a conversation regarding the selection of a desired school through user input using input devices such as the keyboard 209 and mouse 210 shown in Figure 2. The conversation with the user regarding the selection of a desired school takes place, for example, on the desired school consultation screen 500 shown in Figure 5, which will be described later.

[0044] Upon receiving a request to start a conversation, the conversation control unit 302 initiates a conversation with the user regarding the selection of a desired school. Specifically, for example, in the conversation about selecting a desired school, the conversation control unit 302 outputs conversation data indicating questions for the user. These questions are, for example, designed to elicit the user's preferences through natural dialogue. The content of the questions is predetermined, for example, by a scenario. Alternatively, the content of the questions may be generated using a language model such as an LLM.

[0045] Furthermore, the conversation control unit 302 may output conversation data other than questions to the user before and after the conversation data indicating a question to the user. Non-question conversation data may include, for example, greetings, acknowledgments, and explanatory text to the user. The explanatory text may, for example, explain matters related to the question to the user, or it may be supplementary explanations to accurately convey the question to the user.

[0046] The output format of the conversation control unit 302 includes, for example, the display on the display 208 shown in Figure 2, and audio output from a speaker (not shown). More specifically, for example, in the prospective school consultation screen 500 shown in Figure 5 (described later), the conversation control unit 302 outputs conversation data indicating questions to the user as statements from the strategic AI coach. The output conversation data is recorded, for example, as a dialogue history.

[0047] In the following explanation, conversation data representing questions posed to the user may be referred to as "first conversation data."

[0048] The reception unit 301 receives conversation data indicating the user's response to the outputted conversation data. The conversation data to be received is, for example, the conversation data entered immediately after the first outputted conversation data. In addition, if two or more conversation data are entered consecutively after the first outputted conversation data, the reception unit 301 may accept the two or more consecutively entered conversation data.

[0049] Specifically, for example, the reception unit 301 receives conversation data indicating the content of the user's statements through user input using input devices such as a keyboard 209 and a mouse 210. Alternatively, the reception unit 301 may also receive conversation data indicating the content of the user's statements through user voice input using a microphone (not shown). The received conversation data is recorded, for example, as a dialogue history.

[0050] In the following explanation, the conversation data showing the user's responses to the outputted conversation data (first conversation data) may be referred to as "second conversation data."

[0051] The conversation control unit 302 refers to the memory unit 310 and determines whether the content of the statement indicated by the received second conversation data contains any of the keywords stored in the memory unit 310. Here, the memory unit 310 stores the conditions that can be used to search for schools, associating them with keywords related to the selection of the desired school.

[0052] The search criteria available for schools are one of the conditions for narrowing down the list of potential schools. For example, they are used to search for candidate schools (potential target schools) from the school information master DB120 shown in Figure 1. Keywords related to the selection of target schools are, for example, terms that are useful for narrowing down the list of target schools, and can be set arbitrarily in advance.

[0053] Specifically, for example, the conversation control unit 302 refers to the dialogue history and identifies the user's statements from the second conversation data corresponding to the first conversation data output as a statement from the strategic AI coach. The conversation control unit 302 then determines whether the identified statements contain any of the keywords stored in the storage unit 310.

[0054] In this case, the conversation control unit 302 may determine that a keyword is included if the identified statement contains a phrase that exactly matches any of the keywords stored in the memory unit 310. Alternatively, the conversation control unit 302 may determine that a keyword is included if the identified statement contains a synonym or abbreviation of any of the keywords stored in the memory unit 310. Synonyms and abbreviations can be identified, for example, by referring to existing thesauruses or abbreviation dictionaries.

[0055] If the setting unit 303 determines that any of the keywords are included, it sets the conditions stored in the storage unit 310, associated with the keyword, as search conditions for searching for candidate schools (candidate schools). These search conditions for searching for candidate schools are used, for example, to narrow down the list of candidate schools from the school information master DB 120 (see Figure 1).

[0056] In some cases, multiple conditions may be stored in the memory unit 310 in association with keywords contained in the user's utterances. In this case, the setting unit 303 may set the multiple conditions as an AND condition in the search conditions. Alternatively, the setting unit 303 may set the multiple conditions as an OR condition in the search conditions.

[0057] In the following explanation, the search criteria used to find potential schools to apply to may be referred to as "school selection criteria."

[0058] Furthermore, the conversation control unit 302 may repeatedly output first conversation data indicating questions to the user, while switching the questions to the user based on the received second conversation data. Each time the conversation control unit 302 receives second conversation data indicating the user's response to the output first conversation data, it determines whether the content of the response indicated by the received second conversation data contains any of the keywords stored in the storage unit 310.

[0059] Specifically, for example, the conversation control unit 302 may refer to a pre-created scenario, identify questions for the user based on the received second conversation data, and output first conversation data indicating the identified questions. The scenario includes, for example, information that identifies the order in which questions are output to the user. The scenario also includes information that identifies the next question depending on the user's response to the previous question.

[0060] Then, if the setting unit 303 determines that any of the keywords are included, it sets the conditions stored in the storage unit 310 in association with those keywords. At this time, the setting unit 303 may set the new conditions as an AND condition for narrowing down the list of desired schools. Alternatively, the setting unit 303 may set the new conditions as an OR condition for narrowing down the list of desired schools.

[0061] In this way, the information processing device 101 can add conditions that narrow down the list of desired schools by repeatedly outputting questions to the user during a conversation about selecting a school and determining whether or not keywords are included in the user's responses.

[0062] Furthermore, the memory unit 310 may store, in association with each condition that can be used to search for schools, the conditions and the questions and keywords related to the selection of the desired school. In other words, the memory unit 310 may store not only keywords, but also questions output to the user, in association with the conditions that can be used to search for schools.

[0063] In this case, the conversation control unit 302 may refer to the storage unit 310 to determine whether the content of the statement indicated by the received second conversation data contains any of the keywords corresponding to the question indicated by the output first conversation data. Here, the keyword corresponding to the question indicated by the first conversation data is a keyword stored in the storage unit 310 in association with a question that has the same content as the question indicated by the first conversation data.

[0064] Furthermore, the keywords corresponding to the questions indicated by the first conversation data may be keywords stored in the storage unit 310 in association with questions that are similar in content to the questions indicated by the first conversation data. The similarity of the content of the questions may be determined using any existing technology. For example, the conversation control unit 302 may calculate the similarity between the questions using existing technology for calculating the similarity between sentences, and if the similarity is above a threshold, it may determine that the content of the questions is similar.

[0065] Then, if the setting unit 303 determines that any of the keywords are included, it sets conditions in the school selection criteria that correspond to the question shown in the first conversation data and any of the keywords. The conditions that correspond to the question shown in the first conversation data and any of the keywords are conditions stored in the storage unit 310 that associate a question with the same content as the question shown in the first conversation data (or a question with similar content) and any of the keywords.

[0066] In this way, the information processing device 101 stores not only keywords but also questions associated with the conditions that can be used to search for schools, making it possible to set more appropriate conditions for narrowing down the desired schools.

[0067] Furthermore, the memory unit 310 may store, for each of the multiple items used to classify the schools to be searched, a corresponding condition and keywords (or questions and keywords) related to the selection of the desired school, for each condition that can be used to search for the schools to be searched. Here, the items used to classify the schools to be searched can be set arbitrarily.

[0068] Multiple categories may be set, for example, the type of institution, prefecture, faculty / department, academic ranking (deviation score), and entrance examination method. The "type of institution" category is used to classify schools based on who established them. The conditions for the "type of institution" category may include, for example, national, public, national / public, or private.

[0069] The "Prefecture" category is used to classify schools by their location. Conditions for the "Prefecture" category include, for example, each prefecture and region (Kanto, Kansai, Kyushu, Chugoku, Tohoku, Hokkaido). The "Faculty / Department" category is used to classify schools by the types of faculties and departments they offer. Conditions for the "Faculty / Department" category include, for example, science, engineering, agriculture, education, and medicine.

[0070] The "Standard Score" category is used to classify schools based on their standard score. Conditions for the "Standard Score" category include, for example, less than 30, 30 to less than 40, 40 to less than 50, and 50 to less than 55. The "Entrance Examination Method" category is used to classify schools based on their entrance examination method. Conditions for the "Entrance Examination Method" category include, for example, general selection, school recommendation-based selection, and comprehensive selection.

[0071] In this case, the conversation control unit 302 refers to the memory unit 310 and determines whether the content of the statement indicated by the received second conversation data for each of the multiple items contains any of the keywords stored in the memory unit 310. Then, if the setting unit 303 determines that any of the keywords are included for each item, it sets the conditions stored in the memory unit 310 in association with the keyword in the desired school narrowing conditions.

[0072] In this way, the information processing device 101 allows users to set conditions for each item in the criteria for narrowing down their choices of schools by pre-preparing conditions for each item for classifying the schools to be searched.

[0073] The conversation control unit 302 may also output the conditions set for narrowing down the list of preferred schools. Specifically, for example, in a dialogue screen where conversations about selecting preferred schools take place (for example, the preferred school consultation screen 500), the conversation control unit 302 may display the conditions set for narrowing down the list of preferred schools in an area different from the area where conversation data is displayed. This allows the user to check the conditions currently set to narrow down the list of potential preferred schools.

[0074] Furthermore, the reception unit 301 receives instructions to search for prospective schools. Here, the instruction to search for prospective schools is an instruction to search for schools that are candidates for the user's prospective school (prospective school candidates). Specifically, for example, the reception unit 301 receives the instruction to search for prospective schools through user input. Alternatively, the reception unit 301 may also receive the instruction to search for prospective schools through the user's voice input.

[0075] The search unit 304 searches for potential schools (candidate schools) based on the conditions set in the school selection criteria. Specifically, for example, upon receiving a search instruction for a school, it sends a candidate school request to the information provision server 102 shown in Figure 1. The candidate school request includes the school selection criteria.

[0076] When the information server 102 receives a request for candidate schools, it searches for candidate schools based on the school selection criteria included in the request. Specifically, for example, the information server 102 refers to the school information master DB 120 to search for school information of schools that meet the conditions set in the school selection criteria.

[0077] Any existing technology may be used to search for school information that meets the specified criteria. For example, suppose the condition for the item "Establishment Classification" is set to "National." In this case, the information provision server 102 refers to the school information master DB 120 to search for school information of schools whose establishment classification is "National."

[0078] For example, suppose the condition for the "Prefecture" field is set to "Kanto Region". In this case, the information server 102 will refer to the school information master DB 120 to search for school information of schools located in the "Kanto Region". For example, suppose the condition for the "Faculty / Department" field is set to "Education". In this case, the information server 102 will refer to the school information master DB 120 to search for school information of schools that have faculties and departments in the field of education.

[0079] For example, suppose the condition for the item "Standard Deviation" is set to "55 or higher and less than 60". In this case, the information provision server 102 will refer to the school information master DB 120 to search for school information of schools with a standard deviation of "55 or higher and less than 60". For example, suppose the condition for the item "Entrance Examination Method" is set to "Comprehensive Selection". In this case, the information provision server 102 will refer to the school information master DB 120 to search for school information of schools whose entrance examination method is "Comprehensive Selection".

[0080] The information server 102 then sends a response containing the search results and candidate schools to the information processing device 101. The search results are information indicating candidate schools and include some or all of the searched school information. For example, if "Education" is set as the condition for the item "Faculty / Department," the search results may include only information about education-related faculties and departments from the searched school information.

[0081] The search unit 304 can obtain search results included in the candidate school response by receiving the candidate school response from the information provision server 102. The school information master DB 120 may be located in the information processing device 101. In this case, the search unit 304 may refer to the school information master DB 120 to search for school information that satisfies the conditions set in the candidate school narrowing conditions.

[0082] Furthermore, the search unit 304 may search for potential schools (candidate schools) based on the conditions set for narrowing down the desired schools and the user's academic test results. Here, the user's academic test results may be, for example, the results of a regular school (high school) test. Alternatively, the user's academic test results may be the results of a mock exam.

[0083] The user's academic test results may also be obtained through user input using input devices such as a keyboard 209 and a mouse 210. Alternatively, the user's academic test results may be obtained by receiving them from an external computer (for example, an information provision server 102).

[0084] In this case, the search unit 304 sends, for example, a request for candidate schools to the information provision server 102, which includes the criteria for narrowing down the desired schools and the user's academic test results. When the information provision server 102 receives the request for candidate schools, it searches for candidate schools based on the criteria for narrowing down the desired schools and the user's academic test results included in the request.

[0085] Specifically, for example, the information server 102 refers to the school information master DB 120 to search for school information that meets the conditions set for narrowing down the desired schools. Next, based on the user's academic ability test results, the information server 102 identifies school information from the searched school information that matches the user's academic ability.

[0086] Here, a school that matches the user's academic ability may be, for example, a school whose pass rate is estimated to be above a threshold based on the user's academic test results. The threshold can be set arbitrarily and may be set to, for example, around 50%. The information provision server 102 then sends a response of candidate schools including the search results to the information processing device 101. The search results include some or all of the identified school information.

[0087] The search unit 304 can obtain search results included in the candidate school response by receiving the candidate school response from the information provision server 102. This allows the search unit 304 to search for schools that are candidates for the user's desired school (candidate school) while taking the user's academic ability into consideration.

[0088] The conversation control unit 302 outputs the search results. Specifically, for example, the conversation control unit 302 may output the search results as statements made by the strategic AI coach. Alternatively, the conversation control unit 302 may list and display information about potential target schools identified from the search results (e.g., school name, faculty name, department name, etc.).

[0089] Furthermore, the conversation control unit 302 may output conversational data prompting the user to search for prospective schools when the number of conditions set for narrowing down the list of prospective schools exceeds a predetermined number. The predetermined number can be set arbitrarily, for example, to a number of 3 to 5. This allows the conversation control unit 302 to prompt the user to search for prospective schools when the conditions for narrowing down the list of prospective schools to a certain extent have been met.

[0090] The functional units of the information processing device 101 (reception units 301 to search units 304) may be implemented, for example, by the information provision server 102 shown in Figure 1. Alternatively, the functional units of the information processing device 101 (reception units 301 to search units 304) may be implemented by multiple computers within the school matching system 100 (for example, the information processing device 101 and the information provision server 102). In this case, communication between functional units of different computers is performed, for example, by sending and receiving data between functional units via the network 110.

[0091] (Memorized contents of the target school search criteria table 400) Here, using Figure 4, we will explain the contents of the school search criteria table 400 used by the information processing device 101.

[0092] Figure 4 is an explanatory diagram showing an example of the contents stored in the target school search criteria table 400. In Figure 4, the target school search criteria table 400 has fields for item, condition, question, and keyword, and by setting information in each field, the condition information (for example, condition information 400-1 to 400-6) is stored as a record.

[0093] Here, the "Items" section indicates the categories used to classify the schools to be searched. For example, in the case of university entrance exams, the schools to be searched are universities. The "Conditions" section indicates the conditions that can be used to search for schools. The "Questions" section indicates questions related to selecting a target school. The questions registered are those that can help narrow down the list of target schools.

[0094] The keywords represent those relevant to selecting a target school. Keywords should be phrases that are useful for narrowing down the list of target schools. Note that while Figure 4 shows an example where the conditions and keywords match, this is not the only example. For example, synonyms of the words registered in the conditions may be registered as keywords, or words that evoke the words registered in the conditions may be registered.

[0095] For example, condition information 400-1 shows the item "Establishment type", the condition "National / Public", the question "Do you prefer to attend a national / public or private university?", and the keyword "National / Public".

[0096] (Example of a dialogue screen) Next, we will explain an example of the dialogue screen displayed on display 208 when a conversation about selecting a school of choice takes place.

[0097] Figures 5 to 10 are explanatory diagrams showing example screens of the school selection consultation screen. In Figure 5, the school selection consultation screen 500 is an example of a dialogue screen displayed when having a conversation about selecting a school. On the school selection consultation screen 500, the user can converse with the strategic AI coach 501.

[0098] On the school selection consultation screen 500, the statements made by the strategic AI coach 501 are displayed on the left side of the screen. The user's statements are displayed on the right side of the screen. In the example in Figure 5, conversation data 511-513, which shows the statements made by the strategic AI coach 501, are displayed on the school selection consultation screen 500. For example, conversation data 511 shows the statement made by the strategic AI coach 501, "So you're asking about choosing a school?"

[0099] On the prospective school consultation screen 500, users can set their own criteria for narrowing down their prospective schools by operating buttons 502 to 507 using input devices such as a keyboard 209 and a mouse 210. For example, by selecting button 502, the user can set the "National" condition for the "Establishment Category" item as a prospective school narrowing criterion. Then, by selecting button 508 through user input, the user can search for potential prospective schools based on the criteria set for narrowing down their prospective schools.

[0100] On the other hand, it can be difficult for users to determine what criteria to set when searching for potential schools. In this case, by selecting button 509 through user input, users can start a conversation with strategic AI coach 501 regarding the selection of target schools.

[0101] Here, we assume that button 509 is selected.

[0102] In Figure 6, the school consultation screen 500 displays conversation data 611, which shows the user's statements, and conversation data 612 and 613, which show the statements of the strategic AI coach 501. Conversation data 611 is displayed when button 509 is selected. Conversation data 612 and 613 are displayed in response to conversation data 611.

[0103] In Figure 7, conversation data 711-713, showing the content of what the strategic AI coach 501 said, is displayed on the prospective school consultation screen 500. Conversation data 711 provides supplementary explanations to accurately convey the question indicated in conversation data 712. Conversation data 712 indicates a question for the user.

[0104] Specifically, conversation data 712 shows the statement made by strategic AI coach 501, "Which of the following is likely to interest you?" Conversation data 712 corresponds to "first conversation data." Conversation data 713 shows an explanatory text that explains matters related to the question presented in conversation data 712. Specifically, conversation data 713 is information that systematically explains fields of study, and briefly shows what is studied in each field. However, in Figure 7, conversation data 713 is displayed in a simplified form.

[0105] This allows users to follow the guidance of the strategic AI coach 501 and answer questions about topics of interest in a natural flow of conversation.

[0106] Additionally, the school consultation screen 500 displays buttons 721-730. By selecting one of these buttons through user input, users can receive an explanation of what they can learn in the field corresponding to the selected button.

[0107] In Figure 8, the school consultation screen 500 displays conversation data 811 and 815, which show the user's statements, and conversation data 812-814 and 816, which show the statements of the strategic AI coach 501. Conversation data 811 shows the response entered to conversation data 712. Specifically, conversation data 811 shows the user's statement, "I'm interested in education-related fields." Conversation data 811 corresponds to the "second conversation data" in relation to conversation data 712 (first conversation data).

[0108] The conversation data 811 may be input by user operation (text input) using input devices such as a keyboard 209 or mouse 210, or by user voice input using a microphone (not shown). The conversation data 811 may also be input by selecting button 727.

[0109] When the information processing device 101 receives conversation data 811 in response to the output conversation data 712, it refers to, for example, the school search criteria table 400 shown in Figure 4, and determines whether the content of the statements shown in the received conversation data 811 contains any of the keywords corresponding to the questions shown in the output conversation data 712 for each item used to classify the schools to be searched.

[0110] Here, we assume that the content of the statements in conversation data 811 does not contain any keywords corresponding to the questions in conversation data 712. In this case, no conditions are set for narrowing down the target schools.

[0111] Conversation data 812-814 shows the content of statements made by the strategic AI coach 501, based on conversation data 811. Conversation data 812 and 813 show the responses to conversation data 811 and provide explanatory text to explain the "educational" content included in the statements shown in conversation data 811.

[0112] Conversation data 814 represents a question posed to the user. Specifically, conversation data 814 shows the statement made by strategic AI coach 501: "Tell me which areas particularly interest you!" Conversation data 814 corresponds to "first conversation data".

[0113] This allows users to follow the guidance of the strategic AI coach 501 and answer questions about academic fields that interest them in a natural conversational flow.

[0114] Additionally, the prospective school consultation screen 500 displays buttons 821-825. By selecting one of buttons 821-824 through user input, users can receive an explanation of what they can learn in the field corresponding to the selected button. Furthermore, by selecting button 825, users can re-select their area of ​​interest.

[0115] Here, conversation data 815 shows the response entered to conversation data 814. Specifically, conversation data 815 shows the user's statement, "I'm interested in pedagogy." Conversation data 815 corresponds to the "second conversation data" in relation to conversation data 814 (first conversation data).

[0116] The conversation data 815 may be input by user operation (text input) using input devices such as a keyboard 209 or mouse 210, or by user voice input using a microphone (not shown). Furthermore, the conversation data 815 may also be input by selecting button 821.

[0117] When the information processing device 101 receives conversation data 815 in response to the output conversation data 814, it refers to, for example, the desired school search criteria table 400 and determines, for each item, whether the content of the statement shown in the received conversation data 815 contains any of the keywords corresponding to the question shown in the output conversation data 814.

[0118] Specifically, for example, the information processing device 101 refers to the target school search condition table 400 to identify condition information corresponding to the question indicated by the conversation data 814. Here, we assume that condition information 400-5 and 400-6 have been identified. The information processing device 101 then determines whether the content of the statement indicated by the conversation data 815 contains the keywords indicated by the identified condition information 400-5 and 400-6.

[0119] Here, the statement "I'm interested in education" shown in conversation data 811 contains the keyword "education" as indicated by condition information 400-6. Therefore, the information processing device 101 determines that, for the item "Faculty," the statement shown in conversation data 815 contains the keyword corresponding to the question shown in conversation data 814.

[0120] Then, the information processing device 101 sets the condition "Education" indicated by condition information 400-6 as a condition for narrowing down the desired schools for the item "Faculty / Department". In this way, the information processing device 101 can ask the user about the faculty / department they are interested in through dialogue with the strategic AI coach 501 and set the condition "Education" for the item "Faculty / Department".

[0121] Conversation data 816 shows the content of the statements made by the strategic AI coach 501, based on conversation data 815. Conversation data 816 shows the response to conversation data 815 and provides an explanatory text to explain the content of "pedagogy" included in the statements shown in conversation data 815. However, only a portion of the statements shown in conversation data 816 is displayed here.

[0122] In Figure 9, conversation data 911, which shows the content of what the strategic AI coach 501 said, is displayed on the prospective school consultation screen 500. The conversation data 911 shows a message prompting the user to search for prospective schools. The conversation data 911 is output, for example, when the number of conditions set in the prospective school narrowing criteria exceeds a predetermined number.

[0123] Here, in a conversation with Strategic AI Coach 501, the following conditions are set for narrowing down the target schools: "National" for the "Type of Establishment," "Saitama, Chiba, Tokyo, Kanagawa" for the "Prefecture," and "Education" for the "Faculty / Department." The predetermined number is set to "3." In this case, since the number of conditions set for narrowing down the target schools exceeds the predetermined number, conversation data 911 is output.

[0124] In the school consultation screen 500 shown in Figure 9, the user can input a search command for a school by selecting button 921. Furthermore, in the school consultation screen 500, the user can input a button 922 by selecting button 922, for example, to return to the point where conversation data 713 shown in Figure 7 was output, and restart the conversation with the strategic AI coach 501.

[0125] Here, we assume that button 921 is selected and a search instruction for a desired school is entered. In this case, when the information processing device 101 receives the search instruction for a desired school, it outputs the search results based on the conditions set in the desired school narrowing conditions.

[0126] In Figure 10, the search result 1010 is displayed on the prospective school consultation screen 500. The search result 1010 shows an overview of the candidate school "○○ University" that was found based on the conditions set in the prospective school narrowing criteria. By referring to the search result 1010, the user can understand an overview of the school "○○ University".

[0127] In this way, even if users are unable to determine the criteria for narrowing down schools that are right for them, they can easily narrow down the criteria for searching for schools that interest them by answering questions from the Strategic AI Coach 501.

[0128] In the school consultation screen 500 shown in Figure 10, if the user selects button 1021 through user input, they can return to the point where, for example, the conversation data 613 shown in Figure 6 was output and restart the conversation with the strategic AI coach 501. Also, in the school consultation screen 500, if the user selects button 1022 through user input, they can transition to the school setting screen 1100 shown in Figure 11.

[0129] Figure 11 is an explanatory diagram showing an example of the desired school setting screen. In Figure 11, the desired school setting screen 1100 is an example of the operation screen displayed when setting desired schools. On the desired school setting screen 1100, the user can set their first, second, and third choice schools by selecting boxes 1101 to 1103 through user input.

[0130] Here, box 1101 is selected, and "○○ University, Faculty of Education," identified from search result 1010 shown in Figure 10, is set as the first choice.

[0131] (Example of operation of the school matching system 100) Next, we will explain an example of how the school matching system 100 works.

[0132] Figure 12 is a sequence diagram showing an example of the operation of the school matching system 100. In Figure 12, the information processing device 101 performs a school selection condition setting process during a conversation with the user regarding the selection of schools (step S1201). The school selection condition setting process is the process of setting school selection conditions for searching for candidate schools. The specific processing steps of the school selection condition setting process will be described later using Figure 13.

[0133] Next, the information processing device 101 sends a request for candidate schools to the information provision server 102 (step S1202). The request for candidate schools includes the school selection criteria set in step S1201.

[0134] When the information provision server 102 receives a request for candidate schools, it refers to the school information master DB 120 and searches for candidate schools based on the school filtering conditions included in the request (step S1203). The information provision server 102 sends a candidate school response containing the search results to the information processing device 101 (step S1204).

[0135] When the information processing device 101 receives a response from a candidate school, it outputs the search results included in the candidate school response (step S1205) and terminates the series of processes shown in this sequence diagram. As a result, the information processing device 101 can present schools that are candidates for the applicant's desired school.

[0136] Next, using Figure 13, we will explain the specific processing steps for setting the criteria for narrowing down the target schools in step S1201.

[0137] Figure 13 is a flowchart showing an example of the specific processing procedure for setting criteria for narrowing down the list of desired schools. In the flowchart of Figure 13, the information processing device 101 outputs first conversation data indicating questions to the user during a conversation with the user regarding the selection of desired schools (step S1301).

[0138] Furthermore, when outputting the first conversation data, the information processing device 101 may output conversation data other than questions to the user before and after the first conversation data.

[0139] Next, the information processing device 101 determines whether or not it has received second conversation data indicating the user's response to the outputted first conversation data (step S1302). Here, the information processing device 101 waits to receive the second conversation data (step S1302: No).

[0140] Then, when the information processing device 101 receives the second conversation data (step S1302: Yes), it refers to the desired school search criteria table 400 and determines, for each item used to classify the schools to be searched, whether the content of the statement indicated by the received second conversation data contains any of the keywords corresponding to the question indicated by the output first conversation data (step S1303).

[0141] If none of the keywords are included (step S1303: No), the information processing device 101 proceeds to step S1306. On the other hand, if any of the keywords are included (step S1303: Yes), the information processing device 101 refers to the target school search condition table 400 and identifies the conditions corresponding to the question shown in the output first conversation data and any of the keywords (step S1304).

[0142] Next, the information processing device 101 sets the identified conditions as criteria for narrowing down the desired schools (step S1305). Then, the information processing device 101 determines whether or not it has received a request to search for desired schools (step S1306). If it has not received a request to search for desired schools (step S1306: No), the information processing device 101 switches the questions to the user based on the second conversation data received in step S1302 (step S1307) and returns to step S1301. For example, if the user makes a statement that suggests interest in a particular field of study (e.g., an education-related question) in response to a question about that field of study, the information processing device 101 may switch to questions that delve deeper into that field of study. On the other hand, if the user makes a statement that suggests no interest in a particular field of study, the information processing device 101 may switch to questions about a different field of study (e.g., an engineering-related question) or to questions on a completely different topic (e.g., a question about the item "prefecture"). As a result, the user interaction is repeated multiple times, with the questions asked to the user being changed each time.

[0143] On the other hand, if the system receives a request to search for a desired school (step S1306: Yes), the information processing device 101 returns to the step that called the process for setting the conditions for narrowing down the desired school.

[0144] This allows the information processing device 101 to elicit information about the user's interests during a conversation about selecting a school and to set conditions for classifying the schools to be searched.

[0145] Furthermore, if the information processing device 101 has not received the second conversation data after a certain period of time has elapsed in step S1302, it may proceed to step S1306. In addition, the criteria for narrowing down the desired schools may include, for example, the conditions selected by the user's input operation on the desired school consultation screen 500 as shown in Figure 5.

[0146] As described above, the information processing device 101 according to this embodiment can output first conversation data indicating questions to the user during a conversation with the user regarding the selection of a desired school. Furthermore, when the information processing device 101 receives second conversation data indicating the user's response to the output first conversation data, it can refer to the storage unit 310 to determine whether the content of the second conversation data includes any of the keywords stored in the storage unit 310. The storage unit 310 stores, in association with each condition that can be used to search for schools to be searched, the conditions and keywords related to the selection of a desired school. Then, according to the information processing device 101, if any of the keywords are included, the conditions stored in the storage unit 310 in association with the keywords can be set as the desired school narrowing conditions. The desired school narrowing conditions are search conditions for searching for schools that are candidates for the desired school.

[0147] As a result, the information processing device 101 can, through dialogue with an AI (for example, a strategic AI coach 501), elicit information about the user's interests and automatically set search criteria for schools that match the user's preferences, thereby assisting the user in searching for a school of their choice.

[0148] Furthermore, the information processing device 101 can repeatedly execute output, judgment, and setting processes while switching the questions to the user based on the received second conversation data. The output process is the process of outputting the first conversation data indicating the questions to the user. The judgment process is the process of determining whether or not any of the keywords stored in the storage unit 310 are included in the utterances indicated by the second conversation data. The setting process is the process of setting the conditions stored in the storage unit 310 in association with any of the keywords in question as the conditions for narrowing down the desired schools.

[0149] As a result, the information processing device 101 can repeatedly ask the user questions, changing the content of the questions based on the user's responses, thereby eliciting information about the user's interests from various perspectives and setting multiple conditions for searching for a school that matches the user's preferences.

[0150] Furthermore, according to the information processing device 101, when it receives a request to search for a desired school, it can output search results that show candidate schools based on the conditions set in the desired school narrowing criteria.

[0151] This allows the information processing device 101 to present schools that match the user's preferences as potential schools to apply to (candidate schools).

[0152] Furthermore, according to the information processing device 101, when it receives a request to search for a desired school, it can output search results that show candidate schools based on the conditions set for narrowing down the desired schools and the user's academic test results.

[0153] As a result, the information processing device 101 can present schools that are suitable for the user's preferences and for which the user has a reasonable chance of passing the entrance exam, as potential schools to apply to (candidate schools).

[0154] Furthermore, the information processing device 101 can refer to the memory unit 310 to determine whether the content of the statement shown in the second conversation data contains any of the keywords corresponding to the question shown in the first conversation data. However, the memory unit 310 stores the conditions that can be used to search for schools to be searched, associating them with the questions and keywords related to the selection of the desired school. Then, according to the information processing device 101, if any of the keywords are included, a condition corresponding to the question shown in the first conversation data and any of the keywords can be set in the conditions for narrowing down the desired school.

[0155] This allows the information processing device 101 to set conditions by considering not only keywords but also the content of the question, thereby improving the search accuracy when searching for schools that match the user's preferences. For example, if the condition "educational studies" is associated only with the keyword "education," the condition "educational studies" will still be set even if the user answers "I am not interested in education" to the question "Are you not interested in education?". In contrast, the information processing device 101 can prevent the incorrect setting of conditions that do not match the user's preferences by setting conditions while also considering the content of the question.

[0156] Furthermore, according to the information processing device 101, by referring to the memory unit 310, it can determine whether any of the keywords stored in the memory unit 310 are included in the content of the utterance indicated by the received second conversation data for each item used to classify the schools to be searched. However, for each of the multiple items used to classify the schools to be searched, the memory unit 310 stores the conditions that can be used to search for schools and associates them with keywords related to the selection of desired schools. Then, according to the information processing device 101, if any of the keywords are included for each item, the conditions stored in the memory unit 310 in association with those keywords can be set as the conditions for narrowing down the desired schools.

[0157] This allows the information processing device 101 to set conditions that match the user's preferences for each item used to classify the schools to be searched.

[0158] Based on these findings, the search support program, search support method, and information processing device 101 according to the embodiment make it possible for users who have difficulty visualizing a specific school they wish to attend to easily narrow down the search criteria for schools that match their preferences, thereby reducing the burden of selecting a school.

[0159] The search support method described in this embodiment can be implemented by executing a pre-prepared program on a computer such as a personal computer or workstation. This search support program is recorded on a computer-readable recording medium such as a hard disk, flexible disk, CD-ROM, DVD, or USB memory, and is executed when read from the recording medium by the computer. This search support program may also be distributed via a network such as the Internet. [Industrial applicability]

[0160] As described above, this search support program, search support method, and information processing device are useful in computer systems for searching for prospective schools that match the user's preferences, and are particularly suitable for learning support systems that propose the optimal study plan for passing the entrance exam to a prospective school. [Explanation of Symbols]

[0161] 100 Target School Matching System 101 Information Processing Device 102 Information Provision Server 110 Network 120 School Information Master Database 200 buses 201 CPU 202 ROM 203 RAM 204 HDD 205 HD 206 CD-RW drives 207 CD-RW 208 displays 209-key keyboard 210 mice 211 Network I / F 301 Reception Desk 302 Conversation Control Unit 303 Settings Section 304 Search Section 310 Storage section 400 Target School Search Criteria Table 500 School Consultation Screen 501 Strategy AI Coach 502, 503, 504, 505, 506, 507, 508, 509, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 821, 822, 823, 824, 825, 921, 922, 1021, 1022 buttons 511,512,513,611,612,613,711,712,713,811,812,813,814,815,816,911 Conversation data 1010 Search Results 1100 Target School Setting Screen 1101, 1102, 1103 Box

Claims

1. In a conversation with a user regarding the selection of a desired school, the system outputs first conversation data indicating questions for the user. When a second conversation data is received that shows the user's statements in response to the outputted first conversation data, the system refers to a storage unit that stores, for each condition usable for searching for schools, the conditions and keywords related to the selection of the desired school in association, and determines whether or not any of the keywords stored in the storage unit are included in the statements shown in the second conversation data. If it is determined that any of the aforementioned keywords are included, the search conditions for searching for candidate schools for the desired school are set to the conditions stored in the memory unit in association with any of those keywords. A search support program characterized by having a computer perform the processing.

2. The search support program according to claim 1, characterized in that, based on the received second conversation data, the computer repeatedly performs the output process, the judgment process, and the setting process while switching the questions to the user.

3. When a search instruction for the aforementioned target school is received, the system outputs search results indicating candidate schools for the aforementioned target school, based on the conditions set in the search criteria. The search support program according to claim 1, characterized in that it causes the computer to perform the processing.

4. When a search instruction for the desired school is received, the system outputs search results indicating candidate schools for the desired school, based on the conditions set in the search criteria and the user's academic test results. The search support program according to claim 1, characterized in that it causes the computer to perform the processing.

5. The memory unit stores, for each condition that can be used to search for schools, a corresponding relationship between that condition and the questions and keywords related to the selection of the desired school. The process for making the aforementioned determination is: By referring to the memory unit, it is determined whether the content of the statement shown in the second conversation data contains any of the keywords corresponding to the question shown in the first conversation data. The process to be set is, If it is determined that any of the aforementioned keywords are included, the search conditions are set to include conditions corresponding to the question indicated in the first conversation data and any of those keywords. The search support program described in feature 1.

6. The memory unit stores, for each of the multiple items used to classify the schools to be searched, a corresponding condition and keywords related to the selection of the desired school, for each condition that can be used to search for the schools to be searched. The process for making the aforementioned determination is: By referring to the memory unit, for each item, it is determined whether or not the content of the statement indicated by the received second conversation data contains any of the keywords stored in the memory unit. The process to be set is, If it is determined that any of the above keywords are included in each of the above items, the search condition is set to the condition stored in the storage unit in association with that keyword. A search support program according to any one of features 1 to 5.

7. In a conversation with a user regarding the selection of a desired school, the system outputs first conversation data indicating questions for the user. When a second conversation data is received that shows the user's statements in response to the outputted first conversation data, the system refers to a storage unit that stores, for each condition usable for searching for schools, the conditions and keywords related to the selection of the desired school in association, and determines whether or not any of the keywords stored in the storage unit are included in the statements shown in the second conversation data. If it is determined that any of the aforementioned keywords are included, the search conditions for searching for candidate schools for the desired school are set to the conditions stored in the memory unit in association with any of those keywords. A search support method characterized by having a computer perform the processing.

8. In a conversation with a user regarding the selection of a desired school, the system outputs first conversation data indicating questions for the user. When a second conversation data is received that shows the user's statements in response to the outputted first conversation data, the system refers to a storage unit that stores, for each condition usable for searching for schools, the conditions and keywords related to the selection of the desired school in association, and determines whether or not any of the keywords stored in the storage unit are included in the statements shown in the second conversation data. If it is determined that any of the aforementioned keywords are included, the search conditions for searching for candidate schools for the desired school are set to the conditions stored in the memory unit in association with any of those keywords. An information processing apparatus characterized by having a control unit that performs processing.

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