Recruitment support device and recruitment support method

Abstract

To provide a recruitment support device and recruitment support method capable of appropriately recruiting job seekers.SOLUTION: A recruitment support device includes an output part for outputting an editing interface for editing job opening data relating to human resources required by a recruiter, and a control part for calculating a score relating to the quality of the job opening data based on edited contents of the job opening data, where the output part outputs the score.SELECTED DRAWING: Figure 2

Description

Technical Field

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[0001] The present invention relates to a recruitment support device and a recruitment support method.

Background Art

[0002] In recent years, matching services between job seekers and employers have attracted attention. In such matching services, employers register job data related to the human resources they seek in a database, and job seekers apply for the job data they are interested in by referring to the job data (for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, the above-mentioned job data includes various items to be appealed to job seekers (for example, job content, treatment, etc.). Therefore, if the quality of the job data is low, there is a possibility that the human resources required by the employer cannot be appropriately recruited, or that job seekers may not be interested.

[0005] On the other hand, regarding the image of the person required by the employer, the on-site department that needs the human resources grasps it, but the job data is often created by the personnel department. Therefore, it is not easy to create job data for appropriately recruiting the human resources required by the on-site department, and it is also not easy to determine whether the job data is appropriate.

[0006] Therefore, the present invention has been made to solve the above-mentioned problems, and an object thereof is to provide a recruitment support device and a recruitment support method that can appropriately recruit job seekers.

Means for Solving the Problems

[0007] One aspect of the disclosure is a recruitment support device comprising: an output unit that outputs an editing interface for editing job data relating to the personnel sought by the recruiter; and a control unit that calculates a score relating to the quality of the job data based on the edited content of the job data, wherein the output unit outputs the score.

[0008] One aspect of the disclosure is a recruitment support method comprising: step A outputting an editing interface for editing job data relating to the personnel sought by the recruiter; step B calculating a score relating to the quality of the job data based on the edited content of the job data; and step C outputting the score. [Effects of the Invention]

[0009] According to the present invention, it is possible to provide a recruitment support device and a recruitment support method that enable the appropriate recruitment of job seekers. [Brief explanation of the drawing]

[0010] [Figure 1] Figure 1 shows a recruitment support system 100 according to an embodiment. [Figure 2] Figure 2 shows the recruitment support device 30 according to the present invention. [Figure 3] Figure 3 shows an example of profile information according to the present invention. [Figure 4] Figure 4 shows an example of a display configuration according to the embodiment. [Figure 5] Figure 5 shows an example of operation 1 according to the embodiment. [Figure 6] Figure 6 shows an example of operation 2 according to the embodiment. [Figure 7] Figure 7 shows an example of operation 3 according to the embodiment. [Modes for carrying out the invention]

[0011] Embodiments will be described below with reference to the drawings. In the following drawings, identical or similar parts are denoted by the same or similar reference numerals.

[0012] However, it should be noted that the drawings are schematic, and the proportions of each dimension may differ from those in reality. Therefore, specific dimensions should be determined by referring to the explanation below. Furthermore, it is also important to note that there may be differences in the relationships or proportions of dimensions between different drawings.

[0013] [Summary of Disclosure] The recruitment support device for the disclosure summary comprises an output unit that outputs an editing interface for editing job data relating to the personnel sought by recruiters, and a control unit that calculates a score relating to the quality of the job data based on the edited content of the job data, wherein the output unit outputs the score.

[0014] The recruitment support method related to the disclosure summary comprises: step A, outputting an editing interface for editing job data concerning the personnel sought by the recruiter; step B, calculating a score related to the quality of the job data based on the edited content of the job data; and step C, outputting the score.

[0015] The disclosure outlines that the recruitment support device calculates a quality score for job postings based on the edited content of the job postings and outputs the calculated score. With this configuration, recruiters can edit job postings using the editing interface while checking the quality score of the job postings. In other words, they can edit job postings while confirming whether the data is appropriate, and thus recruit suitable job seekers.

[0016] [Embodiment] (Recruitment support system) The recruitment support system according to the embodiment will be described below. Figure 1 is a diagram showing the recruitment support system 100 according to the embodiment.

[0017] As shown in FIG. 1, the employment support system 100 includes a first terminal 10, a second terminal 20, and an employment support device 30. The first terminal 10, the second terminal 20, and the employment support device 30 are connected by a network 200. Although not particularly limited, the network 200 may be constituted by the Internet. The network 200 may include a local area network, may include a mobile communication network, and may include a VPN (Virtual Private Network).

[0018] The first terminal 10 is a terminal used by a job seeker. For example, the first terminal 10 may be a personal computer, may be a smartphone, or may be a tablet terminal. Although not particularly limited, the job seeker may use the first terminal 10 to input the job seeker's profile information.

[0019] The second terminal 20 is a terminal used by an employer. The second terminal 20 may be a personal computer, may be a smartphone, or may be a tablet terminal. Although not particularly limited, the employer may use the second terminal 20 to view the job seeker's profile information.

[0020] The employment support device 30 is a device that supports the recruitment of human resources. The employment support device 30 provides a matching service between job seekers and employers. In an embodiment, the employment support device 30 supports the editing of job offer data. Details of the employment support device 30 will be described later.

[0021] (Employment Support Device)[[ID=I19]] Hereinafter, the employment support device according to the embodiment will be described. FIG. 2 is a diagram showing the employment support device 30 according to the embodiment. As shown in FIG. 2, the employment support device 30 includes a communication unit 31, a management unit 32, and a control unit 33.

[0022] The communication unit 31 is comprised of a communication module. The communication module may be a wireless communication module compliant with standards such as IEEE 802.11a / b / g / n / ac / ax, LTE, 5G, or 6G, or it may be a wired communication module compliant with standards such as IEEE 802.3.

[0023] For example, the communications unit 31 may receive the job seeker's profile information from the first terminal 10. The communications unit 31 may also transmit the job seeker's profile information to the second terminal 20 for the employer to view.

[0024] In this embodiment, the communication unit 31 may be configured as an output unit that outputs an editing interface for editing job data related to the personnel sought by the employer. For example, the communication unit 31 may transmit data to the second terminal 20 for displaying the editing interface on the second terminal 20. Details of the display format shown on the second terminal 20 will be described later (see Figure 4).

[0025] The management unit 32 is composed of storage media such as SSDs (Solid State Drives) and HDDs (Hard Disk Drives), and stores various types of information.

[0026] In this embodiment, the management unit 32 may constitute a management unit for managing the job seeker's profile information. As described above, the profile information may be entered by the job seeker using the first terminal 10.

[0027] While not strictly limited, profile information may include the information shown in Figure 3. As shown in Figure 3, profile information may include desired conditions, current industry, current job title, work history, etc.

[0028] Desired conditions are information about the conditions that the job seeker desires. Desired conditions may include the region in which the job seeker wishes to work (e.g., Tokyo, Osaka, nationwide, overseas, etc.). Desired conditions may include the annual salary that the job seeker wishes to earn (e.g., XX yen or more, XX yen to XX yen, etc.). Desired conditions may include the industry in which the job seeker wishes to work (e.g., manufacturing, information and communication, finance, service industry, etc.). Desired conditions may include the job in which the job seeker wishes to work (e.g., sales, administration, retail, accounting, legal, etc.). While not particularly limited, desired conditions may include items other than those listed above. For example, desired conditions may include the position in which the job seeker wishes to work (e.g., management position, department head position, section chief position, staff position, etc.).

[0029] The current occupation may be information relating to the occupation of the work the job seeker is currently engaged in. If the job seeker is currently unemployed, the current occupation may be information relating to the occupation of the most recent work the job seeker is currently engaged in.

[0030] The current occupation may refer to the occupation of the work the job seeker is currently engaged in. If the job seeker is currently unemployed, the current occupation may refer to the occupation of the most recent work the job seeker is engaged in.

[0031] A resume is information about a job seeker's background. A resume may include information about the job seeker's educational background. A resume may include information about the job seeker's work history. A work history may include a record of the job duties performed by the job seeker. A resume may include information about the job seeker's qualifications. A resume may include information about the job seeker's skills. While not particularly limited, a resume may include items other than those listed above. For example, a resume may include information about the job seeker's strengths (e.g., achievements in professional recognition, personality, etc.).

[0032] The control unit 33 may include at least one processor. The at least one processor may consist of a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), one or more Integrated Circuits, one or more Discrete Circuits, and combinations thereof.

[0033] In this embodiment, the control unit 33 may be configured to calculate a score related to the quality of the job posting data based on the edited content of the job posting data. The control unit 33 may also calculate a score related to evaluation elements for evaluating the job posting data. The evaluation elements may include one or more elements selected from the amount of information contained in the job posting data (hereinafter, amount of information), the expression of the text contained in the job posting data (hereinafter, expression), and the terminology contained in the job posting data (hereinafter, expertise). The terminology contained in the job posting data is terminology that represents the job description of the personnel sought by the employer.

[0034] In this embodiment, the control unit 33 may be configured to identify the number of job seekers who match the job posting based on the edited content of the job posting data and the profile information of the job seekers. The control unit 33 may also identify the expected salary of job seekers who match the job posting data and identify the number of job seekers for each expected salary. In the following, we will mainly describe the case where the expected salary is an expected annual income. The control unit 33 may also identify the expected job type of job seekers who match the job posting data and identify the number of job seekers for each expected job type.

[0035] (Display format) The following describes the display modes according to the embodiment. Figure 4 is a diagram showing an example of a display mode according to the embodiment. Here, the display mode displayed on the second terminal 20 will be described.

[0036] As shown in Figure 4, the display modes may include modes 21A, 21B, 21C, 21D, 21E, and 21F.

[0037] Embodiment 21A includes an editing interface for compiling job data relating to the personnel sought by the employer. Embodiment 21A may include one or more items that constitute the job data. For example, one or more items may include "Specific Job Description," "Mission," "Recruitment Background," "Attractiveness," "Compensation and Benefits," "Employment, Labor, and Work Information," "Career Path," "Organizational Structure," "Desired Candidate Profile," and "Application Requirements."

[0038] "Specific Job Description" may be a section describing the specific details of the industry or job type that the recruiter is seeking will actually be engaged in. "Mission" may be a section describing the guidelines that determine the direction in which the organization (company, department, etc.) will grow. "Recruitment Background" may be a section describing the background that led to the recruitment (filling a vacancy, business expansion, etc.). "Attractiveness" may be a section describing the attractiveness of the organization (company, department, etc.), work, etc. "Compensation and Benefits" may be a section describing compensation (salary, bonus, etc.) and benefits (social insurance, child allowance, commuting allowance, etc.). "Employment, Labor, and Work Information" may be a section describing employment conditions such as regular / non-regular employment, working hours, work location, etc. "Career Path" may be a section describing the path to future positions and duties. "Organizational Structure" may be a section describing the structure of the organization (company, department, etc.). "Desired Candidate Profile" may be a section describing the personality and character of the person needed in the workplace. The "Eligibility Requirements" section may include a section describing the qualifications required for application. It may also include sections describing mandatory qualifications, preferential qualifications, and so on.

[0039] Embodiment 21B is an embodiment that includes a score related to the quality of the job posting data. The score may include scores for each evaluation element (presentation, amount of information, expertise) used to evaluate the job posting data.

[0040] Embodiment 21C is an embodiment that includes the amount of information related to the job posting data. The amount of information may include the number of characters in the job posting data (in Figure 4, character count), the number of sentences in the job posting data, and the average time required to read the job posting data (in Figure 4, average reading time).

[0041] Embodiment 21D may include analysis results (insights in Figure 4) regarding the job posting data. The analysis results may include whether words used uniquely within the organization are used in the job posting data (unique words in Figure 4), or whether words specific to a job type, industry, or sector are used in the job posting data (job-specific words in Figure 4). While not particularly limited, it may be preferable for the proportion of unique words to be low, and for the proportion of job-specific words to be high. In the following, job-specific words mean words specific to at least one of the job type, industry, or sector. Therefore, job-specific words may include so-called industry jargon, etc.

[0042] Embodiment 21E is an embodiment that includes the number of job seekers for each assumed annual income. Although not particularly limited, Embodiment 21E may also be an embodiment in which the number of job seekers for each assumed annual income is represented as a histogram, as shown in Figure 4. However, Embodiment 21E may also be an embodiment in which the assumed annual income or the number of job seekers for each assumed annual income is represented as a continuous value, or an embodiment in which the assumed annual income or the number of job seekers for each assumed annual income is represented as a discrete value. Embodiment 21E may also be an embodiment in which the number of job seekers for each assumed annual income is represented as a number of people.

[0043] Embodiment 21F includes the number of job seekers for each assumed job category. While not particularly limited, Embodiment 21F may also represent the number of job seekers for each assumed job category as a number of people, as shown in Figure 4. However, Embodiment 21F may also represent the number of job seekers for each assumed job category as a histogram.

[0044] Here, aspect 21B may be displayed together with aspect 21A. That is, the score may be output together with the editing interface. Aspect 21B may be displayed in the same window as aspect 21A, or aspect 21B may be displayed in a separate window from aspect 21A depending on the operation to display the score (e.g., a pop-up display).

[0045] Embodiment 21C may be displayed together with Embodiment 21A. Embodiment 21C may be displayed in the same window as Embodiment 21A, or Embodiment 21C may be displayed in a separate window from Embodiment 21A depending on the operation to display the amount of job information (for example, a pop-up display).

[0046] Embodiment 21D may be displayed together with Embodiment 21A. Embodiment 21D may be displayed in the same window as Embodiment 21A, or Embodiment 21D may be displayed in a separate window from Embodiment 21A depending on the operation to display the insight (e.g., a pop-up display).

[0047] Embodiment 21E may be displayed together with Embodiment 21A. That is, the number of job seekers for each assumed annual income may be output together with the editing interface. Embodiment 21E may be displayed in the same window as Embodiment 21A, or Embodiment 21E may be displayed in a separate window from Embodiment 21A depending on the operation to display the number of job seekers for each assumed annual income (for example, a pop-up display).

[0048] Embodiment 21F may be displayed together with Embodiment 21A. That is, the number of job seekers for each assumed job category may be output together with the editing interface. Embodiment 21F may be displayed in the same window as Embodiment 21A, or Embodiment 21F may be displayed in a separate window from Embodiment 21A depending on the operation to display the number of job seekers for each assumed job category (for example, a pop-up display).

[0049] The display modes shown in Figure 4 may include operation buttons for switching the display / hide status of at least one of the modes 21B to 21F.

[0050] The display configuration shown in Figure 4 may include a reflect button to reflect the content edited in configuration 21A. At least one of configurations 21B to 21F may be updated by operating the reflect button.

[0051] (Calculation of score) The calculation of scores according to the embodiment will be described below. As described above, the recruitment support device 30 calculates a score related to the quality of the job posting data based on the edited content of the job posting data. The recruitment support device 30 may also calculate a score related to evaluation elements for evaluating the job posting data. The evaluation elements may include one or more elements selected from information quantity, presentation, and expertise.

[0052] The score for information content may be calculated using the following options:

[0053] In Option 1-1, the information content score may be calculated based on a comparison between the total number of characters in the job data and the appropriate range. For example, the fewer the total number of characters in the job data, which is below the lower limit of the appropriate range, the lower the information content score may be calculated. The more the total number of characters in the job data, which is above the upper limit of the appropriate range, the lower the information content score may be calculated.

[0054] In Option 1-2, the score for information content may be calculated based on the amount of information for each item. For example, the score for each item may be calculated based on a comparison between the number of characters in the item and the appropriate range for the item, and the overall score for information content of the job data may be calculated based on the scores for each item. In such cases, the appropriate range for each item may differ. The overall score for information content of the job data may be calculated based on the scores for each item and the weighted values ​​for each item.

[0055] The score for expression may be calculated using the following options:

[0056] In Option 2-1, the expression score may be calculated based on whether or not the sentences in the job data contain grammatically inappropriate expressions, as determined by analyzing the expressions of those sentences. For example, the more grammatically inappropriate expressions there are, the lower the expression score may be calculated. The expression analysis may be performed using tools such as morphological analysis. The expression analysis may also be performed using machine learning, such as AI (Artificial Intelligence).

[0057] In Option 2-2, the score for expression may be calculated based on the consistency between the item and the text contained within it. For example, if the item "Specific Job Description" contains text other than the specific details of the industry or job that the recruiter is seeking to perform (e.g., text about the ideal candidate profile), the score for expression may be calculated low. Consistency analysis may be performed using tools such as morphological analysis. Consistency analysis may also be performed using machine learning, such as AI.

[0058] In option 2-3, the score for expression may be calculated based on the consistency between sentences included in each of two or more items. For example, if a sentence in the "Mission" item contradicts a sentence in the "Attractiveness" item, the score for expression may be calculated low. The consistency analysis may be performed using tools such as morphological analysis. The consistency analysis may also be performed using machine learning, such as AI.

[0059] The score for expertise may be calculated using the following options:

[0060] In Option 3-1, the expertise score may be calculated by referring to a database containing terminology that describes the job responsibilities of the candidate sought by the employer. For example, if the terminology registered in the database is included in the job posting data, the expertise score may be calculated to be higher.

[0061] Here, the database can be thought of as a dictionary that associates terms representing job duties with the actual jobs. The terms representing job duties may include not only terms actually used in the job posting data, but also terms commonly used in the job. The terms representing job duties may be registered by the recruiter, or by a third party other than the recruiter. The database may be located in the management unit 32 described above, or it may be located in an external device separate from the recruitment support device 30.

[0062] In Option 3-2, the expertise score may be calculated based on the similarity to job data in which the expertise score is determined to be higher than the threshold. The similarity may be identified using machine learning, such as AI. The job data in which the expertise score is determined to be higher than the threshold may be job data in which the score calculated by Option 3-1 is higher than the threshold, or job data selected by the recruiter may be used.

[0063] (Identifying the number of job seekers) The identification of the number of job seekers according to the embodiment will be described below. As described above, the recruitment support device 30 identifies the number of job seekers that match the job data based on the edited content of the job data and the profile information of the job seekers.

[0064] Firstly, the recruitment support device 30 identifies a population of job seekers that matches the edited content of the job posting data from among the profile information (job seekers) of job seekers managed by the management unit 32. For example, the recruitment support device 30 extracts edited content from the edited content of the job posting data that is used to identify the population (e.g., "specific job description," "mission," "recruitment background," "attractiveness," "desired candidate profile," "employment, labor, and working conditions," "application qualifications," etc.). The recruitment support device 30 extracts profile information from the profile information of job seekers that is used to identify the population (e.g., "desired conditions," "current industry," "current occupation," "career history," etc.). The recruitment support device 30 identifies job seekers whose similarity to the extracted edited content and extracted profile information is above a threshold as the population of job seekers (i.e., the number of job seekers).

[0065] The information used to identify the target population may be pre-configured or may be arbitrarily set by the recruiter.

[0066] In the second stage, the recruitment support device 30 identifies the number of job seekers for each expected annual salary or expected job type. The number of job seekers may be identified by the following options.

[0067] Option 4-1 describes the number of job seekers for each expected annual salary. In this case, the recruitment support device 30 extracts information about expected annual salary (for example, desired salary or current salary) from the job seeker's profile information and identifies the expected annual salary for each job seeker included in the population. The recruitment support device 30 then identifies the number of job seekers for each identified expected annual salary.

[0068] In cases where Option 4-1 applies, information regarding annual income (e.g., desired or current annual income included in profile information) does not need to be used in identifying the population. In other words, in the first stage, the population of job seekers may be identified without considering the similarity of information regarding annual income.

[0069] Option 4-2 describes the number of job seekers for each assumed job category. In this case, the recruitment support device 30 extracts information about assumed job categories (e.g., desired job category or current job category) from the job seeker's profile information and identifies the assumed job category for each job seeker included in the population. The recruitment support device 30 then identifies the number of job seekers for each identified assumed job category.

[0070] In cases where Option 4-2 applies, information regarding occupation (e.g., desired occupation or current occupation included in profile information) does not need to be used in identifying the population. In other words, in the first stage, the population of job seekers may be identified without considering the similarity of occupation information.

[0071] In the disclosure described above, for the sake of explanation, the operation of the adoption support device 30 was described in two stages. However, the first and second stages may be treated as a single stage.

[0072] (Example of operation) The following describes an example of operation according to the embodiment. The following mainly describes the operation of the adoption support device 30.

[0073] In Operation Example 1, the operation in which the recruitment support device 30 outputs a score will be explained with reference to Figure 5.

[0074] As shown in Figure 5, in step S10, the adoption support device 30 outputs an editing interface (the embodiment 21A shown in Figure 4) to the second terminal 20.

[0075] In step S12, the adoption support device 30 acquires the input content (editing content) for the editing interface from the second terminal 20.

[0076] In step S14, the recruitment support device 30 calculates a score related to the quality of the job posting data based on the edited content of the job posting data. The recruitment support device 30 may also calculate a score related to the evaluation elements for evaluating the job posting data. The evaluation elements may include one or more elements selected from information quantity, presentation, and expertise.

[0077] In step S16, the recruitment support device 30 outputs a score related to the quality of the job posting data to the second terminal 20 (as shown in the embodiment 21B in Figure 4). The recruitment support device 30 may also output the score along with the editing interface.

[0078] In Operation Example 2, the operation in which the recruitment support device 30 outputs the number of job seekers for each assumed annual salary will be explained with reference to Figure 6.

[0079] As shown in Figure 6, in step S20, the adoption support device 30 outputs an editing interface (the embodiment 21A shown in Figure 4) to the second terminal 20.

[0080] In step S22, the adoption support device 30 acquires the input content (editing content) for the editing interface from the second terminal 20.

[0081] In step S24, the recruitment support device 30 identifies a population of job seekers that are suitable for the job data based on the edited content of the job data and the job seeker's profile information, and also identifies the expected annual salary of job seekers that are suitable for the job data based on the job seeker's profile information.

[0082] In step S26, the recruitment support device 30 outputs the number of job seekers who match the job data for each job seeker's expected annual salary to the second terminal 20 (as shown in the embodiment 21E in Figure 4). The recruitment support device 30 may also output the number of job seekers along with the editing interface.

[0083] In Operation Example 3, the operation in which the recruitment support device 30 outputs the number of job seekers for each assumed job category will be explained with reference to Figure 7.

[0084] As shown in Figure 7, in step S30, the adoption support device 30 outputs an editing interface (the embodiment 21A shown in Figure 4) to the second terminal 20.

[0085] In step S32, the adoption support device 30 acquires the input content (editing content) for the editing interface from the second terminal 20.

[0086] In step S34, the recruitment support device 30 identifies a population of job seekers that are suitable for the job data based on the edited content of the job data and the job seeker's profile information, and also identifies the expected job type of the job seeker that is suitable for the job data based on the job seeker's profile information.

[0087] In step S36, the recruitment support device 30 outputs the number of job seekers who match the job data to the second terminal 20 for each assumed job category of the job seeker (as shown in the embodiment 21F in Figure 4). The recruitment support device 30 may also output the number of job seekers along with the editing interface.

[0088] (Mechanism of Action and Effects) In this embodiment, the recruitment support device 30 may calculate a score related to the quality of the job posting data based on the edited content of the job posting data and output the calculated score. With this configuration, recruiters can edit the job posting data using the editing interface while checking the quality score of the job posting data. In other words, they can edit the job posting data while checking whether the job posting data is appropriate, and can appropriately recruit job seekers.

[0089] In this embodiment, the recruitment support device 30 may output a score along with the editing interface. With this configuration, it is possible to check whether the job posting data is appropriate while performing input (editing job posting data) using the editing interface.

[0090] In this embodiment, the recruitment support device 30 may output the number of job seekers who match the job data, along with an editing interface. With this configuration, recruiters can edit the job data using the editing interface while referring to the job seekers who match the job data. In other words, they can edit the job data while confirming whether the pool of job seekers who match the job data is appropriate, and thus recruit job seekers appropriately.

[0091] In this embodiment, the recruitment support device 30 may output to the second terminal 20 the number of job seekers who fit the job data for each job seeker's expected annual salary. With this configuration, it is easy to grasp any discrepancies between the employer and the job seeker regarding the annual salary in relation to the job data. For example, it is easy to correct the annual salary included in "compensation and benefits" included in the job data. It is also easy to change (expand or shrink) the applicant pool by relaxing the "application requirements" included in the job data, or by changing the content of the "desired candidate profile" included in the job data.

[0092] In this embodiment, the recruitment support device 30 may output to the second terminal 20 the number of job seekers who match the job data for each assumed job type of the job seeker. With this configuration, it is easy to grasp any discrepancies between the employer and the job seeker regarding the job types in the job data. For example, it is easy to change (expand or shrink) the target population by changing the descriptions of "specific job content," "attractiveness," and "career path" included in the job data.

[0093] [Example of change 1] The following describes Example 1 of the modified embodiment. The following mainly describes the differences from the embodiment.

[0094] Specifically, in the embodiment described above, the recruitment support device 30 extracts information regarding expected annual income (for example, desired annual income or current annual income) from the job seeker's profile information and identifies the expected annual income for each job seeker included in the population. The recruitment support device 30 identifies the number of job seekers for each identified expected annual income (Option 4-1). In contrast, Modification Example 1 describes an example of a modification to the method of identifying (estimating) the number of job seekers for each expected annual income. The following options are possible for identifying the number of job seekers for each expected annual income.

[0095] In Option 5-1, the recruitment support device 30 may identify the distribution of expected annual income based on information (e.g., compensation (salary, bonus, etc.)) contained in job data managed by the recruitment support device 30 that includes at least one of the job data to be edited and job data related to the job data to be edited (hereinafter referred to as related job data, etc.). The recruitment support device 30 may also identify the probability for each category of expected annual income (hereinafter referred to as category probability) based on the identified distribution of expected annual income (probability distribution). The recruitment support device 30 may also identify the number of job seekers for each category of expected annual income by multiplying the specific population by the category probability. The specific population may be the total number of job seekers managed by the recruitment support device 30.

[0096] While not particularly limited, related job data may be job data whose similarity to the job data being edited is above a threshold. Similarity may be determined by comparing the two documents (hereinafter referred to as content-based similarity). Similarity may also be determined by the correlation of reactions from job seekers who viewed both (hereinafter referred to as collaborative filtering (memory-based) similarity). Reactions may include viewing the job data, receiving a scout offer related to the job data, or applying for the job data. Similarity may also be determined by a combination of content-based similarity and collaborative filtering similarity.

[0097] In Option 5-2, the recruitment support device 30 may identify the distribution of expected annual income based on information included in the profile information of job seekers who have received scouts regarding relevant job data, job seekers who have applied to relevant job data, and job seekers who have been hired through relevant job data (for example, desired annual income or current annual income). The recruitment support device 30 may also identify the probability for each category of expected annual income (hereinafter referred to as "category probability") based on the identified distribution (probability distribution) of expected annual income. The recruitment support device 30 may also identify the number of job seekers for each category of expected annual income by multiplying the specific population by the category probability. The specific population may be the total number of job seekers managed by the recruitment support device 30.

[0098] In Option 5-3, the recruitment support device 30 may identify annual income based on information included in the profile information managed by the recruitment support device 30 (e.g., desired annual income or current annual income), and identify the number of job seekers for each annual income category for the total number of job seekers. The annual income categories or the number of job seekers for each annual income category may be represented as continuous values, discrete values, or histograms. The recruitment support device 30 may also identify the ratio of relevant job data, etc. to the total number of job data managed by the recruitment support device 30 (hereinafter referred to as the "relevance ratio"). The recruitment support device 30 may also identify the number of job seekers for each expected annual income (category) by multiplying the number of job seekers for each annual income category by the relevance ratio.

[0099] In Example 1 of the changes, we explained the assumed annual income (Pattern 21E), but options 5-1 to 5-3 described above can also be applied to the assumed job type (Pattern 21F). In such cases, you can simply replace the assumed annual income with the assumed job type and apply options 5-1 to 5-3.

[0100] [Other embodiments] Although the present invention has been described by the embodiments described above, the descriptions and drawings that constitute part of this disclosure should not be understood as limiting the invention. Various alternative embodiments, examples, and operational techniques will become apparent to those skilled in the art from this disclosure.

[0101] The disclosure described above provided examples of cases in which at least one of embodiments 21B to 21F may be displayed together with embodiment 21A. However, the disclosure described above is not limited to these examples. At least one of embodiments 21B to 21F may be displayed together with embodiments other than embodiment 21A. That is, two or more embodiments selected from embodiments 21A to 21F may be displayed together.

[0102] The disclosure described above illustrates cases where the number of job seekers for each expected annual income is expressed as the number of people themselves. However, the number of job seekers for each expected annual income may also be expressed as an index. For example, the distribution (probability distribution) of expected annual incomes specified in option 5-1 or option 5-2 described above may be used directly as the number of job seekers for each expected annual income. Similarly, the distribution (probability distribution) of expected occupations specified in option 5-1 or option 5-2 described above may be used directly as the number of job seekers for each expected occupation.

[0103] Although not specifically mentioned in the disclosure above, the number of job seekers for each expected annual salary may be a combination of two or more options selected from options 4-1 and 5-1 to 5-3.

[0104] Although not specifically mentioned in the disclosure above, the number of job seekers for each assumed job category may be a combination of two or more options selected from options 4-1 and 5-1 to 5-3.

[0105] The disclosure described above illustrates a case in which a score is calculated and output for each evaluation element used to evaluate job posting data. However, the disclosure is not limited to this. For example, a score for the entire job posting data (hereinafter referred to as the overall score) may be calculated and output. The overall score may be calculated based on the scores for each evaluation element (hereinafter referred to as the item score). The overall score may be output together with the item score, or it may be output separately from the item score.

[0106] The disclosure described above explains the case where the projected salary is projected annual income. However, the disclosure is not limited to this. The projected salary may be projected annual income including various allowances, or projected annual income excluding various allowances. The projected salary may be projected monthly salary including bonuses, or projected monthly salary excluding bonuses. The projected salary may be projected monthly salary including various allowances, or projected monthly salary excluding various allowances.

[0107] Although not specifically mentioned in the disclosure above, output may be interpreted as display, or as transmission of data for display.

[0108] Although not specifically mentioned in the disclosure above, the term "duties" may be interpreted as work, tasks, responsibilities, roles, etc.

[0109] In the disclosure described above, the score for the quality of the job posting data may be calculated in real time while the job posting data is being edited, in response to the actions of the recruiter, or after the job posting data has been edited.

[0110] In the disclosure described above, the number of job seekers who match the job data may be identified in real time while the job data is being edited, may be identified in response to an action by the recruiter, or may be identified after the job data has been edited.

[0111] Although not specifically mentioned in the disclosure above, a program may be provided that causes a computer to execute each process performed by the recruitment support device 30. Furthermore, the program may be recorded on a computer-readable medium. Using a computer-readable medium makes it possible to install the program on a computer. Here, the computer-readable medium on which the program is recorded may be a non-transient recording medium. The non-transient recording medium is not particularly limited, but may include, for example, a CD-ROM or DVD-ROM.

[0112] Alternatively, a chip may be provided comprising a memory for storing programs for executing each process performed by the employment support device 30, and a processor for executing the programs stored in the memory. [Explanation of symbols]

[0113] 10...First terminal, 20...Second terminal, 30...Recruitment support device, 31...Communication department, 32...Management department, 33...Control unit, 40...Third party, 100...Recruitment support system, 200...Network

Claims

1. A control unit that calculates a score on the quality of the recruitment data based on information contained in the recruitment data on personnel required by the employer; an output unit that outputs the score, The control unit calculates the score based on at least one of the amount of information contained in the job data or the expertise of the personnel desired by the recruiter.

2. A recruitment support device as described in claim 1 or claim 2, wherein when the control unit calculates the score based on the amount of information contained in the job data, the control unit calculates the score based on the result of comparing the number of characters contained in the entire job data with an appropriate range.

3. The recruitment support device of claim 1, wherein when the control unit calculates the score based on the amount of information contained in the job data, the control unit calculates the score based on a comparison result between the number of characters contained in the items that make up the job data and the appropriate range for the items.

4. The recruitment support device of claim 1, wherein when the control unit calculates the score based on the expertise of the personnel desired by the employer, the control unit calculates the score based on the similarity to other job recruitment data in which the score regarding the expertise of the personnel desired by the employer is determined to be higher than a threshold value.

5. A recruitment support device as described in any one of claims 1 to 6, wherein the control unit calculates the score using AI (Artificial Intelligence).

6. The recruitment support device as described in claim 1, wherein the output unit outputs the number of job seekers who match the job recruitment data.

7. The recruitment support device as described in claim 1, wherein the output unit outputs a distribution of expected annual incomes of job seekers.

8. A step A in which a recruitment support device calculates a score on the quality of the recruitment data based on information contained in the recruitment data on personnel required by an employer; A step B in which the recruitment support device outputs the score, The recruitment support method, wherein step A includes a step of calculating the score based on at least one of the amount of information contained in the recruitment data or the expertise of the personnel desired by the recruiter.

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