Search assistance system, search assistance method, and program

Abstract

To provide a search assistance system and the like that can reduce the time and effort required for searching.SOLUTION: According to one aspect of the present invention, a search assistance system is provided. The search assistance system comprises a processor. The processor is configured to be able to execute: a search step of accepting an input of search conditions and searching for registered information regarding an employer or a job seeker based on the search conditions; a priority word extraction step of extracting, as priority words, words related to search words included in the search conditions; and a result display control step of preferentially displaying registered information items that include the priority words among the registered information items that satisfy the search conditions.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a search support system, a search support method, and a program. [Background technology]

[0002] As disclosed in Patent Document 1, a technique is known in which a recruiter (searcher) searches for a job seeker based on job seeker information registered by the job seeker. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 7281024 Summary of the Invention [Problem to be solved by the invention]

[0004] In situations where such employers search for job seekers, or conversely, where job seekers search for job advertisements, if the search results contain a large number of job seekers or job advertisements, they will need to change the search criteria and repeat the search, or browse information on many job seekers and job advertisements, which will increase the time and effort required for the search.

[0005] In view of the above circumstances, the present invention provides a search support system and the like that can reduce the time and effort required for searches. [Means for solving the problem]

[0006] According to one aspect of the present invention, there is provided a search support system. The search support system includes a processor. The processor is configured to be able to execute the following steps. In the search step, input of search conditions is accepted, and registered information relating to employers or job seekers is searched for based on the search conditions. In the priority word extraction step, words related to the search words included in the search conditions are extracted as priority words. In the result display control step, registered information including the priority words is preferentially displayed from among registered information that satisfies the search conditions.

[0007] According to this embodiment, it is possible to reduce the time and effort required for a searcher to perform a search. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a configuration diagram showing a search support system 1. [Diagram 2] 2 is a block diagram showing a hardware configuration of the server device 10. FIG. [Diagram 3] FIG. 2 is a block diagram showing the hardware configuration of a recruiter terminal 20 and a job seeker terminal 30. [Figure 4] FIG. 2 is a block diagram showing functions realized by a server device 10 (control unit 11), a recruiter terminal 20 (control unit 21), and a job seeker terminal 30 (control unit 31). [Diagram 5] FIG. 2 is a diagram showing an example of a tag list TL. [Figure 6] FIG. 13 is a diagram showing an example of a category table CT indicating categories of tag words. [Figure 7] 13 is an example of a search result display screen RD that the result display control unit 117 causes to be displayed on the recruiter terminal 20. [Figure 8] FIG. 2 is an activity diagram showing the flow of information processing (job seeker search processing by a recruiting searcher) executed by search support system 1. [Figure 9] FIG. 1 is an activity diagram showing the flow of information processing (search processing for employers by job seekers) executed by search support system 1. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described with reference to the drawings. Various characteristic features shown in the following embodiments can be combined with each other.

[0010] Incidentally, the program for realizing the software appearing in this embodiment may be provided as a non-transitory computer-readable recording medium, or may be provided so as to be downloadable from an external server, or may be provided so that the program is started on an external computer and its functions are realized on a client terminal (so-called cloud computing).

[0011] In addition, in this embodiment, the term "unit" may include, for example, a combination of hardware resources implemented by a circuit in the broad sense and software information processing that can be specifically realized by these hardware resources. In addition, in this embodiment, various information is handled, and this information is represented, for example, by physical values ​​of signal values ​​representing voltage and current, high and low signal values ​​as a binary bit collection consisting of 0 or 1, or quantum superposition (so-called quantum bits), and communication and calculation can be performed on the circuit in the broad sense.

[0012] In addition, a circuit in the broad sense is a circuit realized by at least appropriately combining a circuit, circuitry, a processor, a memory, etc. In other words, it includes an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)), etc.

[0013] 1. Hardware Configuration This section describes the hardware configuration.

[0014] <Search Support System 1> 1 is a configuration diagram showing a search support system 1. The search support system 1 comprises a communication line 2, a server device 10, a plurality of recruiter terminals 20, and a plurality of job seeker terminals 30. The server device 10, the recruiter terminals 20, and the job seeker terminals 30 are configured to be able to communicate with each other via the communication line 2. The connection between the server device 10, the recruiter terminals 20, and the job seeker terminals 30 and the communication line 2 may be wired or wireless.

[0015] The search support system 1 constitutes part of a recruitment and job search system used by multiple recruiters (a first recruiter U1 and a second recruiter U2) and multiple job seekers (a first job seeker U3 and a second job seeker U4). The search support system 1 mainly performs searches for job seekers by recruiters and searches for recruiters by job seekers. In one embodiment, the search support system 1 is made up of one or more devices or components. These components will be described below.

[0016] <Server device 10> 2 is a block diagram showing a hardware configuration of the server device 10. The server device 10 includes a control unit 11, a storage unit 12, a communication unit 13, and a communication bus 14. The control unit 11, the storage unit 12, and the communication unit 13 are electrically connected to each other inside the server device 10 via the communication bus 14.

[0017] <Control unit 11> The control unit 11 performs processing and control of the overall operation related to the server device 10. The control unit 11 is, for example, a central processing unit (CPU). The control unit 11 realizes various functions related to the server device 10 by reading out a predetermined program stored in the storage unit 12. That is, information processing by software stored in the storage unit 12 can be specifically realized by the control unit 11, which is an example of hardware, and executed as each functional unit included in the control unit 11. These will be described in more detail in the next section. Note that the control unit 11 is not limited to being single, and may be implemented with multiple control units 11 for each function. Also, a combination of these may be used.

[0018] <Storage section 12> The storage unit 12 stores various information defined by the above description. This can be implemented, for example, as a storage device such as a solid state drive (SSD) that stores various programs and the like related to the server device 10 executed by the control unit 11, or as a memory such as a random access memory (RAM) that stores temporarily required information (arguments, arrays, etc.) related to the program calculations. The storage unit 12 stores various programs, variables, etc. related to the server device 10 executed by the control unit 11.

[0019] <Communications Division 13> The communication unit 13 is preferably a wired communication means such as USB, IEEE1394, Thunderbolt (registered trademark), wired LAN network communication, etc., but may also include wireless LAN network communication, mobile communication such as 3G / LTE / 5G, BLUETOOTH (registered trademark) communication, etc. as necessary. In other words, it is more preferable to implement it as a collection of multiple communication means. In other words, the server device 10 may communicate various information from the outside via the communication unit 13 and the network.

[0020] The server device 10 may be in an on-premise form or in a cloud form. As the server device 10 in a cloud form, the above-mentioned functions and processes may be provided in the form of, for example, SaaS (Software as a Service) or cloud computing.

[0021] <Employer Terminal 20> Fig. 3 is a block diagram showing the hardware configuration of the recruiter terminal 20 and the job seeker terminal 30. As shown in Fig. 3A, the recruiter terminal 20 comprises a control unit 21, a memory unit 22, a communication unit 23, an input unit 24, an output unit 25, and a communication bus 26. The control unit 21, the memory unit 22, the communication unit 23, the input unit 24, and the output unit 25 are electrically connected inside the recruiter terminal 20 via the communication bus 26. The explanation of the control unit 21, the memory unit 22, and the communication unit 23 is omitted here as they are the same as the explanation of each unit in the server device 10. Note that the recruiter terminal 20 may be a terminal operated by a human resources agency that interacts with job seekers on behalf of the recruiter.

[0022] <Input section 24> The input unit 24 accepts operation inputs made by the user. The operation inputs are transferred as command signals to the control unit 21 via the communication bus 26. The control unit 21 may execute predetermined control or calculations based on the transferred command signals as necessary. The input unit 24 may be included in the housing of the recruiter terminal 20, or may be externally attached. For example, the input unit 24 may be implemented as a touch panel integrated with the output unit 25. When the input unit 24 is implemented as a touch panel, the user can input tap operations, swipe operations, and the like to the input unit 24. As the input unit 24, a switch button, a mouse, a track pad, a QWERTY keyboard, and the like can be adopted instead of a touch panel.

[0023] <Output section 25> The output unit 25 displays a screen of a graphical user interface (GUI) that can be operated by the user. The output unit 25 may be included in the housing of the recruiter terminal 20, or may be attached externally. Specifically, the output unit 25 may be implemented as a display device such as a CRT display, a liquid crystal display, an organic EL display, or a plasma display. It is preferable that these display devices are implemented by selectively using them according to the type of recruiter terminal 20.

[0024] <Job Seeker Terminal 30> 3B, the job seeker terminal 30 includes a control unit 31, a memory unit 32, a communication unit 33, an input unit 34, an output unit 35, and a communication bus 36. The control unit 31, the memory unit 32, the communication unit 33, the input unit 34, and the output unit 35 are electrically connected inside the job seeker terminal 30 via the communication bus 36. Descriptions of the control unit 31, the memory unit 32, the communication unit 33, the input unit 34, and the output unit 35 will be omitted as they are the same as the descriptions of the respective units in the recruiter terminal 20.

[0025] 2. Functional configuration In this section, the functional configuration of the present embodiment will be described. Information processing by the software stored in the storage unit 12 is specifically realized by the control unit 11, which is an example of hardware, and can be executed as each functional unit included in the control unit 11 (a processor included in the search support system 1).

[0026] FIG. 4 is a block diagram showing functions realized by the server device 10 (control unit 11), the recruiter terminal 20 (control unit 21), and the job seeker terminal 30 (control unit 31).

[0027] As shown in Fig. 4A, server device 10 (control unit 11) includes a basic display control unit 111, a recruiter registration unit 112, a job seeker registration unit 113, a tag assignment unit 114, a search unit 115, a priority word extraction unit 116, a result display control unit 117, and an artificial intelligence unit 118. As shown in Fig. 4B, recruiter terminal 20 (control unit 21) includes a display unit 211 and an operation reception unit 212. As shown in Fig. 4C, job seeker terminal 30 (control unit 31) includes a display unit 311 and an operation reception unit 312.

[0028] <Basic display control unit 111> The basic display control unit 111 is configured to display various information on the recruiter terminal 20 or the job seeker terminal 30. For example, the basic display control unit 111 displays resumes and curriculum vitae created by the job seeker, job advertisements and scout documents created by the recruiter, search results by the search unit 115, etc. on the display unit 211 of the recruiter terminal 20 or the display unit 311 of the job seeker terminal 30.

[0029] <Employer Registration Section 112> The recruiter registration unit 112 is configured to register recruiters to use the service. For example, the recruiter registration unit 112 receives input from the operation reception unit 212 of the recruiter terminal 20, and stores in the storage unit 12 recruiter information related to the recruiter to which the recruiting searcher belongs or which the recruiter represents.

[0030] Employer information is registered information about employers. Employer information includes job posting information (position being recruited, job description, application qualifications, expected annual salary, working conditions, etc.), organization information (name, location, representative, business description, etc.), and employment agency information (name, etc.). This makes it possible to assign tags based on the employer information and to search for employer information.

[0031] Employers include for-profit entities (e.g., companies), non-profit entities (e.g., cooperatives, foundations), and public entities (e.g., local governments). Employer searchers include human resources personnel, hiring managers, and recruiters of the organization (employer), and recruitment agencies that act as agents of the organization to mediate between job seekers and employers. Recruitment agencies are also called headhunters, agents, etc.

[0032] <Job Seeker Registration Department 113> The job seeker registration unit 113 is configured to register job seekers to use the service. For example, the job seeker registration unit 113 accepts input from the operation acceptance unit 312 of the job seeker terminal 30, and stores job seeker information about the job seeker in the storage unit 12. The job seeker information is registered information about the job seeker, such as the job seeker's resume, curriculum vitae, or other profile information. This makes it possible to assign tags and search for job seeker information based on the job seeker's experience, skills, and other job seeker information.

[0033] A "resume" is a document that mainly describes a job seeker's profile, current situation, educational background, employment history, desired working conditions, etc., while a "career history" is also called a résumé, and is a document in which a job seeker conveys to an employer his or her work history, experience, skills, qualifications, etc. regarding his or her past work. Job seeker information may also include conditions such as the job seeker's desired industry and occupation.

[0034] <Tag assignment unit 114> The tag assignment unit 114 is configured to assign tags to registered information based on the contents of the registered information of the employer or job seeker prior to a search by the search unit 115. This enables the search for registered information in the result display control unit 117 and preferential display in the search results. Specifically, the tag assignment unit 114 assigns a tag corresponding to a tag word described in a tag list to registered information that includes the tag word. In other words, the tag assignment unit 114 assigns a tag corresponding to a tag word to employer information or job seeker information that includes a tag word corresponding to a tag described in a tag list prepared in advance, based on employer information or job seeker information. Here, a tag list is a list in which one or more tags are described, and a tag word is a word described in a tag (i.e., a word corresponding to a tag). Therefore, one or more tag words are described in the tag list. In addition, when the tag assignment unit 114 assigns a tag to registered information, it is not limited to cases where the word contained in the registered information and the tag word are a perfect match, but may also include cases where they are a partial match, or where the word contained in the registered information is a synonym, similar word, or a word with a spelling variation of the tag word.

[0035] The tag assignment unit 114 instructs the artificial intelligence to assign tags to the recruiter information or job seeker information, inputs the recruiter information or job seeker information to the artificial intelligence, and has the artificial intelligence assign tags. Specifically, the tag assignment unit 114 extracts recruiter information or job seeker information containing tag words listed in the tag list from the recruiter information or job seeker information to be searched, instructs the artificial intelligence to assign tags corresponding to the included tag words to each of the extracted recruiter information or job seeker information, and inputs the recruiter information or job seeker information and the tag list to the artificial intelligence, thereby having the artificial intelligence assign tags to the recruiter information or job seeker information.

[0036] For example, if the registration information to which tags are to be added is a resume of a job seeker, the tagging unit 114 instructs the AI ​​to add tags to the resume, inputs the resume to the AI, and has the AI ​​add tags. This makes it possible to assist in searching for job seekers based on words contained in their resumes.

[0037] FIG. 5 is a diagram showing an example of the tag list TL. Each row of the tag list TL represents one tag, and the tag list TL includes tag words corresponding to each tag. Furthermore, the tag words may be associated with groups of tags and written in the tag list. Examples of tag words include words related to the "market" such as "BtoB", "SaaS", and "EC", words related to "products" such as "cloud", "accounting system", and other individual service names and product names, words related to the "environment" such as "Python", "cloud", and "venture", words related to "skills" such as "development", "design", "machine learning", and "bookkeeping".

[0038] Tag words are classified into categories according to the manner in which they are used in the registered information of employers or job seekers. FIG. 6 is a diagram showing an example of a category table CT showing categories of tag words. In the example of FIG. 6, categories A1-A4, B1-B4, C1-C4 are set as "mode of use in registered information" by combining the "job type" that the job posting is recruiting for or the job seeker has experience in, and the context in which the tag word is used in the employer information or job seeker information (for example, the item in which the tag word is written in the job posting, resume, or curriculum vitae). Note that tag words may also be classified into categories by items other than those listed here.

[0039] Categories A1-A4 are categories related to the occupation of "sales", and for example, category A1 is classified as a tag word used in a context related to "market" in sales jobs. Categories B1-B4 are categories related to the occupation of "engineer", and categories C1-C4 are categories related to the occupation of "management". The category table CT in FIG. 6 is an example of a tag word category, and the tag word category may have a more detailed hierarchical structure. For example, subcategories such as "tools" and "company phase" may exist as lower-level categories of "environment", and tag words may be classified in association with the subcategories. For example, the tag word "Python" may be classified into the subcategory of "environment" called "tools", and the tag word "venture" may be classified into the subcategory of "environment" called "company phase".

[0040] Some tag words are classified into multiple categories. For example, regarding "Service X," if "Service X" is sold as a salesperson, the tag word for "Service X" is classified into category A2. On the other hand, if the same "Service X" is used for development, the tag word for "Service X" is classified into category B4. Also, for example, the tag word "SaaS" is related to multiple job types, so it is classified into categories A1, B1, and C1.

[0041] When tagging the registered information, the tag assigning unit 114 assigns a tag score to the tag based on the tag word corresponding to the tag. The tag score is set for each registered information according to the usage form in the registered information of the tag word corresponding to the tag attached to the registered information. For example, even if a tag corresponds to the same tag word "service X", if the usage form of "service X" in the resume of job seeker P and job seeker Q is different, the tag score in the resume of job seeker P may be 10 points and the tag score in the resume of job seeker Q may be 8 points. Since the category of the tag word assigned is different depending on the location and context in which the tag word is used in the resume, the tag score set may be different even if the same tag is assigned. This allows the display priority of the registered information in the result display control unit 117 to be set according to the usage form of the tag word.

[0042] Specifically, the tag score is set according to the category of the tag word to which the tag corresponds. That is, as shown in FIG. 5, a score for each category is set for each tag word. For example, the tag word "BtoB" is classified into category A1 and category B2. For this tag word, a score of 10 points is set for a tag attached to registered information in which "BtoB" is used in a manner of use corresponding to category A1, and a score of 8 points is set for a tag attached to registered information in which "BtoB" is used in a manner of use corresponding to category B1. This allows the display priority in the result display control unit 117 to be adjusted by setting individual tag scores.

[0043] The tag assigning unit 114 assigns a tag to registered information when a tag word corresponding to a tag is included in the registered information in a usage pattern corresponding to a category to which the tag word is classified. In other words, even if a tag word is included in registered information in which the tag word is not used in a usage pattern corresponding to a category to which the tag word is classified, a tag corresponding to the tag word is not assigned. For example, a tag corresponding to the tag word "BtoB" in FIG. 5 is not assigned to registered information in which "BtoB" is used in a usage pattern corresponding to a category other than category A1 and category B1 (a category in which the tag word "BtoB" is not classified). In addition, for example, a tag word classified into a specific occupation (e.g., "sales") is not assigned to a tag corresponding to the tag word even if it is used in registered information of another occupation (e.g., "management"). This prevents registered information in which a tag word is used in a usage pattern other than the one required for a search from being preferentially displayed.

[0044] The tag words written in the tag list TL are created by instructing the artificial intelligence to create tag words from words contained in the registered information or words used in searching the registered information. This allows the tag list to be created without relying on the subjectivity of the system designer. Tag lists may be created separately for employer information and job seeker information. Tag lists may also be created separately for each content of an item contained in the employer information or job seeker information, such as by industry or job type. For example, a tag list for "sales" and a tag list for "technical jobs" may be created separately.

[0045] Specifically, the tag assignment unit 114 instructs the AI ​​to select tag words based on the registered information to be searched (employer information or job seeker information) or the frequency of use in searches of registered information, and inputs words contained in the registered information or words used in searches of registered information to the AI ​​to select frequently used words in the registered information or searches of registered information as tag words. This allows registered information containing frequently used words to be preferentially displayed in the search results.

[0046] Furthermore, the tag assigning unit 114 may further instruct the artificial intelligence to select tag words based on their appropriateness as words to be associated with tags, and may input criteria for appropriateness as tag words (e.g., training data of appropriate tag word samples) to the artificial intelligence to select tag words. This makes it possible to exclude words that are inappropriate as tags to be used in searching for information on employers or job seekers, such as non-objective words such as "smart," from tag words, and to prevent tags corresponding to such words from being assigned.

[0047] <Search section 115> The search unit 115 is configured to accept input of search conditions and to search for registered information related to recruiters or job seekers based on the search conditions. Specifically, the search unit 115 searches for recruiters or job seekers who satisfy the search conditions based on the recruiter information or job seeker information registered by the recruiter registration unit 112 and the job seeker registration unit 113 (i.e., by referring to the database stored in the storage unit 12), based on search conditions including a search word input by a searcher from the recruiter terminal 20 or the job seeker terminal 30.

[0048] <Priority word extraction unit 116> The priority word extraction unit 116 extracts, as priority words, words related to the search word included in the search criteria used for the search by the search unit 115. "Words related to the search word" include, for example, synonyms, similar words, paraphrases, words expressing higher concepts, words expressing lower concepts, co-occurring words of the search word, etc., and also includes the search word itself.

[0049] Specifically, the priority word extraction unit 116 extracts, as priority words, tag words related to the search word from among the tag words corresponding to the tags attached to the registered information. This allows registered information attached with tags highly related to the search word to be preferentially displayed at the top of the search results. The "tag words related to the search word" are tag words that are the same as the search word, tag words that are synonymous or similar to the search word, tag words that paraphrase the search word, tag words that represent a higher-level concept of the search word, tag words that represent a lower-level concept of the search word, tag words that are co-occurring words with the search word, etc.

[0050] For example, consider a case where the tag word "Vue.js" is listed in the tag list and "Javascript" is entered as a search word. If the search word "Vue.js" is often used simultaneously with the search word "Javascript" (i.e., there is a high degree of co-occurrence), the priority word extraction unit 116 extracts the tag word "Vue.js" related to the search word "Javascript" as a priority word.

[0051] The priority word extraction unit 116 instructs the artificial intelligence to extract words related to the search word as priority words, inputs the search word to the artificial intelligence, and causes the artificial intelligence to extract the priority words. Specifically, the priority word extraction unit 116 instructs the artificial intelligence to extract priority words from a tag list based on the search word, and inputs the search word and priority word candidates (i.e., the tag list) to the artificial intelligence, causing the artificial intelligence to output the priority words. This improves the accuracy of extraction of priority words based on the search word.

[0052] The priority word extraction unit 116 sets a boost score for the priority word based on the relevance between the search word and the priority word. For example, the priority word extraction unit 116 sets a boost score based on the co-occurrence between the search word and the priority word in the search history for the registered information stored in the storage unit 12. Specifically, the priority word extraction unit 116 sets a higher boost score (score multiplied by the tab score) for the priority word as the co-occurrence between the search word and the priority word (how frequently they are used simultaneously in searches for job seeker information or job seeker information) is higher. Note that when the search word and the priority word match, the co-occurrence (boost score) is the highest. In addition, even for the same word, the boost score of the priority word may differ depending on the relevance with the search word. For example, for the word "AAA", the boost score as the priority word for the search word "BBB" may be set to 10 points, and the boost score as the priority word for the search word "CCC" may be set to 5 points. In this case, the word "AAA" has a higher co-occurrence with the word "BBB" than with the word "CCC." This increases the total score of the search word directly entered by the searcher and the highly relevant tags, making it easier for registered information that is closer to the searcher's (employer or job seeker) desired criteria to be preferentially displayed.

[0053] <Result display control unit 117> The result display control unit 117 is configured to preferentially display registered information including the priority word extracted by the priority word extraction unit 116, among the registered information satisfying the search conditions searched by the search unit 115. In other words, the result display control unit 117 preferentially displays registered information to which a tag corresponding to the priority word is attached.

[0054] Specifically, the result display control unit 117 determines the display order of the registered information according to the tag score set for the tag corresponding to the priority word. This makes it possible to determine the display order of employer information or job seeker information in the search results based on the tag score for each tag. Therefore, registered information that is close to the information that the searcher is looking for can be displayed at the top of the search results, and registered information that is more meaningful to the searcher can be displayed preferentially. This allows the searcher to reach the employer information or job seeker information that he or she is looking for without spending time and effort.

[0055] When one piece of registered information contains multiple tag words written in the tag list, multiple tags are attached to this registered information. In registered information to which multiple tags corresponding to such priority words are attached, the total of the tag scores of the tags corresponding to the priority words set for each tag becomes the tag score of this registered information. In the search results, registered information with high tag scores is preferentially displayed. In other words, registered information is displayed in descending order of tag score. Note that the number of tags corresponding to the priority words attached to the registered information may be the tag score of the registered information.

[0056] Furthermore, the result display control unit 117 determines the display order of the registered information according to the tag score set for the tag corresponding to the priority word and the boost score set for the priority word. This allows the display priority in the search results to be determined using the tag score (basic score) set for the tag word as well as the boost score (additional score) for the search word used in the search. This makes it possible to adjust the display priority in the search results according to not only the content of the registered information but also its relevance (for example, co-occurrence) to the search criteria entered by the searcher.

[0057] Specifically, the result display control unit 117 preferentially displays registered information having a large value obtained by multiplying the tag score set for the tag corresponding to the priority word by the boost score set for the priority word. This allows the weighting based on the relevance to the search criteria entered by the searcher to be increased in the display priority of the search results.

[0058] For example, for registered information tagged with "Vue.js" (including "Vue.js"), if the tag score set for the tag corresponding to "Vue.js" is 10 points and the boost score set for the priority word "Vue.js" extracted from the input search word "Javascript" is 5 points, the result display control unit 117 sets the total score of this registered information to 50 points. The result display control unit 117 displays a list of registered information sorted in descending order of total score as a search result on the employer terminal 20 or the job seeker terminal 30. In other words, registered information with a higher total score is displayed higher, making it easier for searchers to find it. For registered information with multiple tags, the total score is calculated by adding up the product of the tag score of each tag and the boost score of the corresponding priority word.

[0059] 7 is an example of a search result display screen RD that the result display control unit 117 causes to be displayed on the recruiter terminal 20. On the search result display screen RD, multiple searched registered information are displayed in a list from the top in descending order of total score. Note that the tag words, priority words, tag scores, and boost scores do not have to be displayed on the search result display screen RD.

[0060] <Artificial Intelligence Department 118> The artificial intelligence unit 118 is configured to receive input from each functional unit and return the instructed output. The artificial intelligence used by the server device 10 in each functional unit may be a common one, or may be prepared individually for each functional unit.

[0061] The artificial intelligence unit 118 is an AI (Artificial Intelligence) equipped with language models such as Transformers including GPT (Generative Pretrained Transformer, including GPT-1, GPT-2, and GPT-3), BERT (Bidirectional Encoder Representations from Transformers), and BART (Bidirectional and Auto-regressive Transformer), and Recurrent Neural Networks (RNN), and includes a generative AI.

[0062] The language model is an example of a learning model based on a machine learning algorithm. Specific examples of machine learning algorithms include nearest neighbor methods, naive Bayes methods, decision trees, support vector machines, and deep learning using neural networks. The artificial intelligence unit 118 can apply the above algorithms as appropriate.

[0063] The artificial intelligence unit 118 has, as artificial intelligence, a trained model constructed by a learning method such as supervised learning, unsupervised learning, or self-supervised learning. In supervised learning, machine learning is performed using training data (training data). The training data is composed of a pair of input data for learning and output data (correct answer data). In addition, the language model may not only be one trained for a specific task, but also a general-purpose model that can be used for a wide range of tasks.

[0064] The artificial intelligence unit 118 includes, as the artificial intelligence, a general-purpose learning model for natural language processing, such as a large-scale language model (LLM) that has learned a huge amount of data. Such a general-purpose learning model includes a language model that can handle various tasks without fine tuning by one-shot learning, few-shot learning, or the like. The artificial intelligence used in each functional unit of the control unit 11 may be a separate learning model, or may be a common general-purpose learning model.

[0065] For example, when separate learning models are used, one learning model is trained to take registration information and a tag list as input and output tagged registration information, and another learning model is trained to take search words and a tag list as input and output priority words. Also, for example, when a general-purpose learning model is used, a prompt is instructed to take registration information and a tag list as input and output tagged registration information, and a prompt is instructed to take search words and a tag list as input and output priority words.

[0066] The artificial intelligence included in the artificial intelligence unit 118 can perform additional learning. For example, the artificial intelligence unit 118 learns whether the presented search conditions were used in an actual search by a searcher. In other words, the artificial intelligence unit 118 performs additional learning and fine-tuning using a teacher data set that combines the presented search conditions with labeled actual search conditions as feedback for the search conditions created and presented by the artificial intelligence. As a result, the search conditions output from the learning model are optimized and presented to the user.

[0067] <Display section> The display unit 211 of the recruiter terminal 20 and the display unit 311 of the job seeker terminal 30 each display a screen indicated by the screen data transmitted from the server device 10.

[0068] <Operation reception section> The operation acceptance unit 212 of the recruiter terminal 20 accepts operations by a user (recruiter side searcher) who uses the recruiter terminal 20. The operation acceptance unit 312 of the job seeker terminal 30 accepts operations by a user (job seeker) who uses the job seeker terminal 30.

[0069] 3. Information processing method This section describes an information processing method of the server device 10. This information processing method is executed by a computer, with each unit of the server device 10 acting as each step.

[0070] Specifically, this information processing method includes a search step, a priority word extraction step, and a result display control step. In the search step, input of search conditions is accepted, and registered information relating to employers or job seekers is searched for based on the search conditions. In the priority word extraction step, words related to the search words included in the search conditions are extracted as priority words. In the result display control step, registered information including the priority words is preferentially displayed among registered information that satisfies the search conditions.

[0071] 8 is an activity diagram showing the flow of information processing (job seeker search processing by a job-employer searcher) executed by search support system 1. Below, the information processing will be explained along with each activity in this activity diagram.

[0072] The job seeker search process begins with the input of search conditions by the recruiting searcher. The recruiting searcher inputs search conditions for the job seeker's resume, curriculum vitae, etc., at the recruiting party terminal 20 (activity A101). The server device 10 accepts the input of the search conditions and searches for job seeker information based on the search conditions (search step, activity A102).

[0073] Next, the server device 10 extracts priority words related to the search words entered by the employer searcher as search conditions (priority word extraction step, activity A103). The extraction of priority words may be performed in parallel with the search for job seeker information, or may be performed before the search for job seeker information. After extracting the priority words, the server device 10 compares the tags of the searched job seeker information with the priority words (activity A104).

[0074] Next, the server device 10 causes the recruiter terminal 20 to display the search results in which job seeker information that has been given a tag corresponding to the priority word is displayed preferentially among the searched job seeker information (result display control step, activity A105). As a result, the recruiter terminal 20 presents the search results sorted based on the tag (activity A106).

[0075] 9 is an activity diagram showing the flow of information processing (search processing for recruiters by a job seeker) executed by search support system 1. Below, the information processing will be explained along with each activity in this activity diagram.

[0076] The search process for employers begins with the input of search conditions by the job seeker. The job seeker inputs search conditions for job advertisements and the like at the job seeker terminal 30 (activity A201). The server device 10 accepts the input of the search conditions and searches for employer information based on the search conditions (search step, activity A202).

[0077] Next, the server device 10 extracts priority words related to the search words entered by the job seeker as search conditions (priority word extraction step, activity A203). The extraction of priority words may be performed in parallel with the search for recruiter information, or may be performed before the search for recruiter information. After extracting the priority words, the server device 10 compares the tags of the searched recruiter information with the priority words (activity A204).

[0078] Next, the server device 10 displays the search results on the job seeker terminal 30, in which the information of employers that have been searched for and have been tagged with a tag corresponding to the priority word are preferentially displayed (result display control step, activity A205). As a result, the search results sorted based on the tags are presented on the job seeker terminal 30 (activity A206).

[0079] 4. Effect The effects of this embodiment can be summarized as follows: That is, the effort and time required for a searcher to perform a search can be reduced.

[0080] Although the embodiment of the present invention has been described above, the present invention is not limited to this, and can be modified as appropriate without departing from the technical concept of the invention.

[0081] 5.Other In the above embodiment, the server device 10 performs various storage and control, but multiple external devices may be used instead of the server device 10. That is, various information and programs may be distributed and stored in multiple external devices using block chain technology or the like. In particular, the artificial intelligence unit 118 may be an external configuration of the server device 10. In that case, the artificial intelligence unit 118, which is an external configuration, is configured to receive input from each functional unit of the server device 10 and return the instructed output to the server device 10.

[0082] The aspect of the present embodiment is not limited to the search support system 1, and may be an information processing method or a program. The search support method includes each step of the search support system 1. The program causes a computer to execute each step of the search support system 1.

[0083] It may be provided in any of the following ways:

[0084] (1) A search support system comprising a processor configured to execute each of the following steps: a search step, receiving input of search conditions and searching for registered information relating to employers or job seekers based on the search conditions; a priority word extraction step, extracting words related to search words included in the search conditions as priority words; and a result display control step, preferentially displaying registered information including the priority words among the registered information that satisfies the search conditions.

[0085] (2) In the search support system described in (1) above, in the priority word extraction step, a tag word related to the search word is extracted as the priority word from among tag words corresponding to tags attached to the registered information, and in the result display control step, the registered information to which the tag corresponding to the priority word is attached is displayed preferentially.

[0086] (3) In the search support system described in (2) above, in the result display control step, the display order of the registered information is determined according to a tag score set for the tag corresponding to the priority word.

[0087] (4) In the search support system described in (3) above, the tag score is set for each registered information depending on the usage pattern in the registered information of the tag word corresponding to the tag attached to the registered information.

[0088] (5) In the search support system described in (4) above, the tag words are classified into categories according to the manner of use in the registration information, and the tag score is set according to the category of the tag word.

[0089] (6) A search support system according to any one of (3) to (5) above, wherein in the priority word extraction step, a boost score is set for the priority word based on the relevance between the search word and the priority word, and in the result display control step, a display order of the registered information is determined based on the tag score set for the tag corresponding to the priority word and the boost score set for the priority word.

[0090] (7) In the search support system described in (6) above, the processor is further configured to execute the following steps: in the storage step, a search history for the registered information is stored; and in the priority word extraction step, the boost score is set based on the co-occurrence between the search word and the priority word in the search history.

[0091] (8) In the search support system described in (6) or (7) above, in the result display control step, the registered information having a larger value obtained by multiplying the tag score set for the tag corresponding to the priority word by the boost score set for the priority word is displayed preferentially.

[0092] (9) In the search support system described in any one of (1) to (8) above, in the priority word extraction step, an artificial intelligence is instructed to extract a word related to the search word as the priority word, the search word is input to the artificial intelligence, and the artificial intelligence is caused to extract the priority word.

[0093] (10) In the search support system described in any one of (2) to (9) above, the processor is configured to further execute the following steps: in a tagging step, the tag is assigned to the registered information based on the content of the registered information.

[0094] (11) In the search support system described in (10) above, the tag words are classified into categories according to the manner of use in the registered information, and in the tag assignment step, if the tag word corresponding to the tag is included in the registered information in a manner of use corresponding to the category to which the tag word is classified, the tag is assigned to the registered information.

[0095] (12) A search support system according to any one of (10) to (11) above, wherein the registration information is a resume of the job seeker, and in the tagging step, an artificial intelligence is instructed to assign the tag to the resume, the resume is input to the artificial intelligence, and the artificial intelligence is caused to assign the tag.

[0096] (13) In the search support system described in any one of (10) to (12) above, in the tag assignment step, the tag corresponding to the tag word described in the tag list is assigned to the registered information containing the tag word, and the tag word is created by instructing an artificial intelligence to create the tag word from a word contained in the registered information or a word used in searching the registered information, and having the artificial intelligence create the tag word.

[0097] (14) In the search support system described above in (13), the tag words are selected based on the registered information or frequency of use in searches of the registered information.

[0098] (15) A search support system according to any one of (1) to (11) above, wherein the registration information is the job seeker's resume, curriculum vitae, or other profile information.

[0099] (16) A search support method comprising the steps of the search support system according to any one of (1) to (15) above.

[0100] (17) A program that causes a computer to execute each step of the search support system described in any one of (1) to (15) above. Of course, this is not the case.

[0101] Finally, although various embodiments according to the present disclosure have been described, these are presented as examples and are not intended to limit the scope of the invention. The novel embodiment can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. The embodiments and their modifications are included in the scope and spirit of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0102] 1: Search support system 2: Communication lines 10: Server device 11: Control section 12: Storage section 13: Communications Department 14: Communication bus 20: Recruiter terminal 21: Control section 22: Storage section 23: Communications Department 24: Input section 25: Output section 26: Communication bus 30: Job Seeker Terminal 31: Control section 32: Storage section 33: Communications Department 34: Input section 35: Output section 36: Communication bus 111: Basic display control unit 112: Employer Registration Department 113: Job Seeker Registration Department 114: Tagging section 115: Search section 116: Priority word extraction unit 117: Result display control section 118: Artificial Intelligence Department 211:Display section 212: Operation reception section 311: Display section 312: Operation reception section

Claims

1. A search support system, comprising: A processor is provided. The processor is configured to execute the following steps: In the search step, input of search conditions is accepted, and registered information relating to employers or job seekers is searched for based on the search conditions. In the priority word extraction step, words related to the search words included in the search conditions are extracted as priority words; In the result display control step, the search support system displays, with priority, the registered information including the priority word among the registered information satisfying the search condition.

2. 2. The search support system according to claim 1, In the priority word extraction step, a tag word associated with the search word is extracted as the priority word from among tag words corresponding to the tag attached to the registered information; In the result display control step, the registered information to which the tag corresponding to the priority word is attached is preferentially displayed.

3. 3. The search support system according to claim 2, In the result display control step, a display order of the registered information is determined according to a tag score set for the tag corresponding to the priority word.

4. 4. The search support system according to claim 3, A search support system, wherein the tag score is set for each registered information according to the manner in which the tag word corresponding to the tag attached to the registered information is used in the registered information.

5. 5. The search support system according to claim 4, The tag words are classified into categories according to the manner of use in the registration information; A search support system, wherein the tag score is set according to the category of the tag word.

6. 4. The search support system according to claim 3, In the step of extracting a priority word, a boost score is set for the priority word based on a relevance between the search word and the priority word; In the result display control step, a search support system determines the display order of the registered information based on the tag score set for the tag corresponding to the priority word and the boost score set for the priority word.

7. 7. The search support system according to claim 6, The processor is further configured to perform the steps of: In the storing step, a search history for the registration information is stored; A search support system, wherein in the priority word extraction step, the boost score is set based on a co-occurrence between the search word and the priority word in the search history.

8. 7. The search support system according to claim 6, In the result display control step, the search support system preferentially displays the registered information that has a larger value obtained by multiplying the tag score set for the tag corresponding to the priority word by the boost score set for the priority word.

9. 2. The search support system according to claim 1, In the priority word extraction step, a search support system instructs an artificial intelligence to extract words related to the search word as the priority word, inputs the search word into the artificial intelligence, and causes the artificial intelligence to extract the priority word.

10. 3. The search support system according to claim 2, The processor is further configured to perform the steps of: In the tagging step, the tag is assigned to the registered information based on the contents of the registered information.

11. The search support system according to claim 10, The tag words are classified into categories according to the manner of use in the registration information; In the tag assignment step, a search support system assigns a tag to the registered information if the tag word corresponding to the tag is included in the registered information in a usage form corresponding to the category to which the tag word is classified.

12. The search support system according to claim 10, The registration information is a resume of the job seeker, In the tag assignment step, a search support system instructs an artificial intelligence to assign the tag to the resume, inputs the resume into the artificial intelligence, and causes the artificial intelligence to assign the tag.

13. The search support system according to claim 10, In the tag assignment step, the tag corresponding to the tag word written in the tag list is assigned to the registered information including the tag word, A search support system instructing an artificial intelligence to create tag words from words contained in the registered information or words used in searching the registered information, and having the artificial intelligence create the tag words.

14. The search support system according to claim 13, A search support system, wherein the tag words are selected based on the registered information or frequency of use in searches of the registered information.

15. 2. The search support system according to claim 1, The search support system, wherein the registration information is the job seeker's resume, curriculum vitae, or other profile information.

16. A search support method, comprising: A search support method comprising the steps of the search support system according to any one of claims 1 to 15.

17. A program, A program causing a computer to execute each step of the search support system according to any one of claims 1 to 15.

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