KR102615206B1 - A system for providing job competency information based on learning activity records including job seeker job competency acquisition statement for each job in the luxury watch and jewelry industry - Google Patents

Abstract

The present invention relates to a system for providing job competency information based on learning activity records including job competency acquisition descriptions for each job in the luxury watch and jewelry industry. Specifically, the job seeker terminal performs learning using learning data provided to improve job competency. In, a learning outcome creation request unit that requests creation of a learning outcome for already performed learning data; A learning outcome analysis unit that electronically documents learning outcomes written in natural language on the job seeker's terminal according to the performance of the function of the learning outcome creation request department, and analyzes the electronically documented learning outcomes based on artificial intelligence technology including at least a natural language processing algorithm; And, by receiving the analysis results of the learning outcomes from the learning outcomes analysis department, evaluating the job seeker's learning performance on the learning data, and updating the job competency of the individual job seeker based on the evaluated learning performance. It is characterized by including a job competency management department that manages the job competency of.

Description

Job competency information provision system based on learning activity records including job competency acquisition descriptions for job seekers in the luxury watch and jewelry industry AND JEWELRY INDUSTRY}

The present invention relates to a system for providing job competency information based on learning activity records including job competency acquisition descriptions of job seekers for each job in the luxury watch and jewelry industry. Specifically, the present invention relates to a job competency information provision system based on learning activity records including job seeker job competency acquisition descriptions for each job in the luxury watch and jewelry industry. It is related to technology that manages competency, intuitively provides job competency information of job seekers to employers seeking employment, and matches jobs appropriate to the job accordingly.

It is a very important task for a company to hire talent that meets the capabilities required to perform jobs in the industrial field. In the past, companies recognized academic background as an important criterion for judging job performance ability regardless of the job, and often did not provide sufficient job descriptions or clear hiring criteria during the hiring process.

Meanwhile, in the hiring process of these companies, there were many cases where talent unsuitable for the job was hired, so there was a problem that a considerable amount of time and money had to be spent on job training until the hired talent was put into practice.

In addition, the problem was worsening as there were many cases where talented people employed in the field failed to adapt to their jobs and left the company or changed jobs early, causing even greater losses to companies and talented people. As a result, the government was forced to provide regulations for each job in the industrial field. National competency standards (NCS) were introduced to identify the required knowledge, skills, and abilities and use them as an important standard when recruiting talent, and not only to national agencies, public agencies, and educational institutions, but also to private companies. The goal is to spread it.

Meanwhile, as big data analysis technologies have developed recently, many attempts have been made to improve job mismatching by using NCS.

As an example, Korean Patent Publication No. 10-2018-0082329 discloses a technology for an automatic job matching service that includes job competency prediction and a computing device using the same. However, in the case of the above-mentioned prior art, a candidate who does not have job competency is disclosed. It is only a technology that applies basic job competency functions to job competent people so that the goal of automatic job matching is predicted and applied in a future-oriented manner, and as in the present invention, job competency learning necessary to acquire job competency in the luxury watch and jewelry industry is carried out and There was a limitation in that it was difficult to use as a technology to collect and request the creation of necessary learning outcomes for each job to ensure that job seekers have job capabilities, or to promote matching between job seekers and hiring entities.

Accordingly, the present invention is based on the evaluation log for the evaluation of learning outcomes when the evaluation of learning outcomes, including the job seeker's self-introduction, portfolio, and job competency description, etc., for each job in the luxury watch and jewelry industry is performed on the job seeker's terminal. The primary purpose is to provide the technology to enable capabilities to be managed.

In addition, the present invention provides the job competency information of job seekers managed based on learning outcomes to the hiring entity seeking employment, so that the job competency information of job seekers is provided in an intuitive form so that the hiring entity can identify the talent needed. The second purpose is to provide technology that enables accurate and rapid hiring.

In order to achieve the above-mentioned purpose, job competency of job seekers for each job in the luxury watch and jewelry industry is implemented in a computing device including one or more processors and one or more memories storing instructions executable by the processor according to an embodiment of the present invention. The system for providing job competency information based on learning activity records, including job skills, requests the job seeker terminal who has performed learning using the learning data provided to improve job competency to create learning outcomes for the already performed learning data. Writing request section; A learning outcome analysis unit that electronically documents learning outcomes written in natural language on the job seeker's terminal according to the performance of the function of the learning outcome creation request department, and analyzes the electronically documented learning outcomes based on artificial intelligence technology including at least a natural language processing algorithm; And, by receiving the analysis results of the learning outcomes from the learning outcomes analysis department, evaluating the job seeker's learning performance on the learning data, and updating the job competency of the individual job seeker based on the evaluated learning performance. It is characterized by including a job competency management department that manages the job competency of.

At this time, the above-mentioned learning outcome creation request unit is an input interface that requests creation of learning outcomes from the job seeker terminal immediately after learning of the learning data is completed at the job seeker terminal and after a preset threshold time has elapsed from the time the learning data is completed. It is desirable to provide so that more than one learning outcome is created for one learning data.

In addition, the learning outcome analysis unit described above is a learning outcome recorded after a preset threshold time has elapsed from the time learning of the learning data is completed, compared to the first learning outcome, which is a learning outcome recorded immediately after learning of the learning data is completed. It is desirable to set the weight for the analysis of the second learning outcome relatively higher.

In addition, the above-mentioned learning data includes learning contents about attitudes, knowledge, skills, and equipment that are job performance requirements, and the input interface provided to the job seeker terminal to create learning outcomes includes attitudes that are job performance requirements, Since each recording area is allocated for knowledge, skills, and equipment, it is desirable to have the job seeker's terminal record detailed learning outcomes for job performance requirements in the allocated recording area.

In addition, the above-mentioned learning outcome analysis department tokenizes the texts written in each recording area of the learning outcomes through a natural language processing algorithm when learning outcomes for job performance requirements are recorded through the input means of the job seeker's terminal, and the job competency management department, It is desirable to evaluate the job seeker's learning performance by comparing the similarity between tokenized keywords and key keywords already stored as learning goals in the learning data.

In addition, the above-mentioned learning outcome analysis unit, when learning outcomes for job performance requirements are recorded through the input means of the job seeker's terminal, tokenizes the texts included in the learning outcomes through a natural language processing algorithm and then analyzes the tokenized keywords. When applied to the analysis algorithm, it is desirable for the job competency management department to evaluate the job suitability of job seekers based on the sentiment analysis results of tokenized keywords.

In addition, the input interface provided to the job seeker terminal for creating the above-mentioned learning outcomes is further allocated as a recording area, where the learning impressions of the learning data already performed by the job seeker terminal are recorded, and the record where the learning impressions are recorded The area is divided into a recording area where the most accomplished and unachieved learning content is recorded, and in the learning outcome analysis section, the texts written in the recording area corresponding to the most accomplished learning content and the unaccomplished learning content are recorded. The goal is to tokenize the texts written in the corresponding record area through a natural language processing algorithm, identify the job competencies corresponding to each tokenized keyword, and assign weight to the individual job competency of the job seeker managed by the job competency management department. desirable.

In addition, the system for providing job competency information based on learning activity records, including job competency acquisition descriptions for job seekers for each job in the luxury watch and jewelry industry, is based on the results of analyzing multiple learning outcomes created on subscriber terminals during a pre-set critical period. It further includes a result report generation unit that generates a result report on the job competency of the individual, and the result report on the job competency of the individual job seeker generated in the result report generation unit is at least one of the companies and organizations that have registered the job seeker as a person of interest. It is desirable to provide it to an employment entity terminal that includes one or the other.

In addition, the result report provided to the hiring entity terminal described above includes a word cloud visualized using one or more keywords extracted from a plurality of learning outcomes created on the job seeker terminal, and multiple word clouds are created for each job performance requirement, Each keyword that makes up the word cloud includes keywords extracted from learning outcomes, and it is desirable to differentiate the format set for the keywords according to the job competency of the individual job seeker.

In addition, the above-mentioned result report generation unit allows individual viewing of multiple learning outcomes created on the job seeker terminal, but when a request for generating a summary of multiple learning outcomes is received from the hiring entity terminal, the plurality of learning outcomes are preset. It is desirable to apply a text summary algorithm to summarize a number of sentences included in a plurality of learning outcomes into a preset number of sentences so that the summary is provided to the hiring entity's terminal.

According to one embodiment of the present invention, in the present invention, when learning data is performed on the job seeker terminal, the process of determining the job seeker's learning performance, such as requesting the job seeker terminal to create learning outcomes, is repeated to be more based on the job seeker's learning activity. This has the effect of making it possible to manage job competency.

In addition, according to an embodiment of the present invention, in the present invention, the job seeker's learning performance is evaluated by analyzing the learning outcomes created on the job seeker's terminal, and the job suitability of the job seeker can be determined, thereby matching the hiring entity and the job seeker. This has the effect of increasing the city matching success rate.

In addition, according to an embodiment of the present invention, in providing the job seeker's job competency information managed based on learning outcomes to the hiring entity seeking employment, the job seeker's job competency information is utilized in a word cloud, etc. By providing it in a more intuitive form, it can be expected to have the effect of enabling employers to hire the talent they need more quickly.

Figures 1 and 2 are diagrams of a system for providing job competency information based on learning activity records, including job seeker job competency acquisition descriptions for each job in the luxury watch and jewelry industry according to an embodiment of the present invention.
Figure 3 is an example of an input interface for recording learning outcomes provided to a job seeker terminal according to an embodiment of the present invention.
Figure 4 shows an example of a learning outcome created on a job seeker's terminal according to an embodiment of the present invention, and an example of a keyword set as a learning goal in the learning data.
Figure 5 is an example of a word cloud related to the job competency of an individual job seeker included in a result report according to an embodiment of the present invention.
Figure 6 is a conceptual diagram of a text summary algorithm that summarizes text included in a plurality of learning outcomes into a preset number of sentences according to an embodiment of the present invention.
7 is an example of the internal configuration of a computing device according to an embodiment of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS Various embodiments and/or aspects are now disclosed with reference to the drawings. In the following description, for purposes of explanation, numerous specific details are set forth to facilitate a general understanding of one or more aspects. However, it will also be appreciated by those skilled in the art that this aspect(s) may be practiced without these specific details. The following description and accompanying drawings set forth in detail certain example aspects of one or more aspects. However, these aspects are illustrative and some of the various methods in the principles of the various aspects may be utilized, and the written description is intended to encompass all such aspects and their equivalents.

As used herein, “embodiment,” “example,” “aspect,” “example,” etc. may not be construed to mean that any aspect or design described is better or advantageous than other aspects or designs. .

Additionally, the terms "comprise" and/or "comprising" mean that the feature and/or element is present, but exclude the presence or addition of one or more other features, elements and/or groups thereof. It should be understood as not doing so.

Additionally, terms containing ordinal numbers, such as first, second, etc., may be used to describe various components, but the components are not limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, a first component may be referred to as a second component, and similarly, the second component may be referred to as a first component without departing from the scope of the present invention. The term and/or includes any of a plurality of related stated items or a combination of a plurality of related stated items.

In addition, in the embodiments of the present invention, unless otherwise defined, all terms used herein, including technical or scientific terms, are as commonly understood by a person of ordinary skill in the technical field to which the present invention pertains. It has the same meaning. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and unless clearly defined in the embodiments of the present invention, have an ideal or excessively formal meaning. It is not interpreted as

The present invention relates to a system for providing job competency information based on learning activity records, including job competency acquisition descriptions of job seekers for each job in the luxury watch and jewelry industry. Specifically, job seekers' self-introductions, portfolios, and job competency descriptions for each job in the luxury watch and jewelry industry. The first purpose is to provide technology to manage the job seeker's job competency based on the evaluation log for the learning outcome evaluation when the evaluation of learning outcomes, including the like, is performed on the job seeker's terminal. In addition, in the present invention, in providing the job competency information of job seekers managed based on learning outcomes to the hiring entity seeking employment, the job competency information of the job seeker is provided in an intuitive form to provide the talent needed by the hiring entity. The second purpose is to provide technology that enables more accurate and rapid adoption.

Hereinafter, a more detailed description of the present invention will be provided with reference to the accompanying drawings, and multiple drawings may be simultaneously referred to to explain one or more technical features or components constituting the invention.

With reference to Figure 1, let us look at the configuration of a learning activity record-based job competency information provision system 10 including job seeker job competency acquisition descriptions for each job in the luxury watch and jewelry industry according to an embodiment of the present invention.

As shown in Figure 1, in the present invention, a learning product creation request unit requests the job seeker terminal 20, which has performed learning using the learning data provided to improve job capabilities, to create a learning outcome for the previously performed learning data. (11), artificial intelligence technology that electronically documents learning outcomes written in natural language at the job seeker terminal 20 according to the performance of the function of the learning outcome creation request unit 11, and includes at least a natural language processing algorithm for the electronically documented learning outcomes. The learning outcome analysis unit 12, which analyzes the learning outcomes based on the analysis results, receives the analysis results of the learning outcomes from the learning outcome analysis unit 12, evaluates the job seeker's learning achievement level for the learning data, and adds the evaluated learning achievement level to the learning outcome analysis unit 12. It includes a job competency management department (13) that manages the job competency of the individual job seeker by updating the job competency of the individual job seeker based on the job competency.

First, looking at the above-mentioned learning outcome creation request unit 11 in detail, the above-mentioned learning data mentioned in the learning outcome creation request unit 11 refers to the concept of learning data generated based on the National Competency Standards (NCS). It can be understood to include learning about attitudes, knowledge, skills and equipment that are performance requirements.

As an example, in the present invention, it is preferable that the above-described learning data is understood as a concept of learning data for training experts in the watch jewelry field. However, in another embodiment of the present invention, the above-described learning data is used in fields other than the watch jewelry field. It may also be understood as a concept including learning data for other specialized fields, and the present invention is not limited thereto.

In addition, the above-mentioned learning data is a plurality of learning data converted into a curriculum and provided to the job seeker terminal 20 according to a schedule on the curriculum, or pre-stored learning data is provided whenever a request to perform learning is received from the job seeker terminal 20. Learning methods such as:

In addition, the above-described learning outcome creation request unit 11 may request creation of a learning outcome for the already performed learning data whenever it detects that the job seeker terminal 20 has completed the execution of the learning data.

At this time, in the present invention, in order to request the creation of a learning outcome, an input interface for the job competency acquisition description can be provided to the job seeker terminal 20 as shown at 100 in FIG. 3 to request the creation of a learning outcome.

Specifically, in the input interface provided to the job seeker terminal 20 to create learning outcomes, each recording area for attitudes, knowledge, skills and equipment required for job performance is assigned, allowing the job seeker terminal 20 to Detailed learning outcomes for job performance requirements can be recorded in the recording area.

As an example, when the learning data includes learning content about the materials used for the exterior of the watch and the watch case, the record area for attitude among the job performance requirements includes the material used for the exterior of the watch and the watch case. For jobs in charge of materials, a record of what attitude is required may be requested, and in the knowledge record area among the job performance requirements, a record of working knowledge of the materials used for the exterior of the watch and the case of the watch may be requested. Among the job performance requirements, records of diagnosing and repairing the exterior of the watch and the case of the watch may be requested in the recording area for technology or equipment.

Preferably, the learning product creation request unit 11 of the present invention provides the above-described input interface for requesting the job seeker terminal 20 to create a learning outcome immediately after learning of the learning data is completed in the job seeker terminal 20. It can function to determine the job seeker's learning performance based on the learned learning data.

In other words, the learning outcome creation request unit 11 requests the job seeker terminal 20 to create a learning outcome related to the learning data (i.e., requests creation of the first learning outcome) immediately after completing learning about the learning data, and the job seeker terminal 20 requests the creation of a learning outcome related to the learning data. You can judge whether you have understood the learning content well.

However, in the above-described embodiment, the description was limited to the embodiment of requesting the job seeker's terminal to write a job competency acquisition description as a learning outcome. However, in another embodiment of the present invention, the job seeker's portfolio is created along with the writing of the job competency acquisition description described above. By requesting, the portfolio created on the job seeker's terminal may be managed by including it as one of the learning outcomes, but the present invention is not limited to this.

In addition, in a more preferred embodiment of the present invention, a preset threshold time (for example, 30 to 60 minutes) is elapsed from the time when the learning product creation request unit 11 described above completes learning of the learning data in the job seeker terminal 20. After the elapse, the job seeker terminal 20 may be requested to re-create the learning outcome (i.e., request the creation of a second learning outcome) so that two or more learning outcomes are created for one learning data.

In other words, this requests the creation of learning outcomes immediately after learning is performed on one learning data and after a preset threshold time has elapsed from the time learning was performed, so that at least two learning outcomes are created in one learning data. By doing so, an evaluation is made of how much the job seeker understands and remembers the learning content included in the learning data by comparing the learning outcomes created initially with the learning outcomes created after a critical time, thereby evaluating the job seeker's learning performance. It can be done.

Meanwhile, at this time, when the learning log for job performance requirements is recorded through the input means of the job seeker terminal 20, the above-described learning outcome analysis unit 12 of the present invention records the learning outcomes by recording area (i.e., job performance requirements). Texts written in (star record area) are tokenized through a natural language processing algorithm, and the job competency management department (13) compares the similarity between the tokenized keywords and key keywords already stored as learning goals in the learning data to determine the job seeker's learning performance. will be evaluated.

As an embodiment, referring to FIG. 4, an example of a learning outcome created in the job seeker terminal 20 is shown at 200 in FIG. 4, and an example of a learning outcome created in the job seeker terminal 20 is shown at 210 in FIG. 4, and is stored in learning data performed on the job seeker terminal 20. Examples of key keywords are shown.

At this time, the learning outcome analysis unit 12 may use analysis algorithms such as morphological analysis and syntactic analysis to analyze the learning outcomes written in natural language on the job seeker terminal 20. Specifically, the morphological analysis described above may be performed on the learning outcomes. The process of analyzing the character data contained in and separating them into minimum meaning units called morphemes is performed, and performs the function of distinguishing roots, prefixes/suffixes, and parts of speech.

In addition, the above-mentioned syntactic analysis performs the function of analyzing (or parsing) the structure of the sentence. To put it simply, the learning outcomes input from the job seeker terminal 20 (40) include sentence components such as subject, verb, and object. It can be understood as analyzing the sentence structure according to sentence components by determining whether or not it is possible.

As an example, when the learning outcome analysis unit 12 analyzes the sentence "The store must obtain the customer's signature to consent to the collection of personal information" shown at 400 in FIG. 4 based on a morpheme analysis algorithm, the root As a (substantive morpheme), separate "watch repair request form, writing, store, consent to personal information collection, customer, signature, required", and add "in, to, of, to, to~", etc. with suffixes ( After separating them into grammatical morphemes), the root corresponding to the actual morpheme is used as the main keyword, and the training performance can be judged by comparing the similarity with the key keyword set in the learning data.

At this time, as a means of determining how similar the above-mentioned main keyword is to the core keyword, a simple method of checking whether the main keyword includes all the core keywords may be used, but a cosine similarity judgment algorithm may be used to determine the similarity between the two keyword groups. Similarity can also be judged.

Specifically, the cosine similarity judgment algorithm described above is an algorithm that obtains the vector of each word in a sentence (or based on the actual morpheme within the sentence) and determines the similarity using the cosine angle between the vectors. Generally, the cosine value is -1 to 1. Since it has a value between two vectors, the more the directions of the two vectors are the same, the more similar they can be considered. If the angle is vertical, 0 is returned, and if they are completely different, -1 is returned to judge the similarity.

As an example, Table 1 below shows the main keywords and key keywords, and applying them to the cosine similarity judgment algorithm is as follows.

watch repair
request letter write store Privacy
Consent to collection sir) autograph (signature) essential main
keyword One One One One One One One main point
keyword One One 0 One One One One

The formula for applying the cosine similarity judgment algorithm is as follows,

Formula 1:

By interpreting the above formula,

= (1*1)+(1*1)+(1*0)+(1*1)+(1*1)+(1*1)+(1*1) = 6, = * = Since ≒ 6.48, the similarity can be calculated as 6/6.48=0.926, that is, the similarity between the two sentences is 92.6%.

In other words, in the present invention, the similarity between the main keywords of the learning outcomes entered by the job seeker as described above and the key keywords set in the daily learning data is determined, and when the similarity between the keywords is more than 90%, the job seeker's learning performance is judged to be very excellent. If it is 80% or more but less than 90%, it is judged as excellent, if it is 65 to less than 80%, it is judged as average, and if it is less than 65%, the training performance is judged to be poor, and the training performance is judged differentially to determine the individual job seeker's This means that learning outcomes can be managed.

Meanwhile, in order to more systematically analyze the job seeker's learning performance, the learning outcome analysis unit 12 of the present invention includes a first learning outcome, which is a learning outcome recorded immediately after learning of the learning data is completed, and a first learning outcome, which is a learning outcome recorded immediately after learning of the learning data is completed. When determining a job seeker's learning performance by analyzing the second learning outcome, which is a learning outcome recorded after a preset critical time has elapsed, the analysis weight of the first learning outcome and the second learning outcome is varied. By setting this, the job seeker's learning performance can be analyzed more closely.

As an example, in the present invention, the weight for the analysis proportion of the second learning outcome is set to be relatively higher than the analysis proportion for the first learning outcome, and how much the job seeker learns from the learning data after a certain period of time. By increasing the proportion of analysis on whether the job seeker remembers, it is possible to determine whether the learning content of the learning data performed by the job seeker has been formed into long-term memory.

As a specific example, in the present invention, the analysis ratio of the first and second learning outcomes is set to 2:8, 3:7, or 4:6 to more closely analyze the job seeker's learning performance. However, in the case where the analysis proportion of the second learning outcome is greater than that of the first learning outcome, it is preferable that it be understood as a concept included in the present invention.

As another embodiment, when learning information about job performance requirements is recorded through the input means of the job seeker terminal 20, the learning outcome analysis unit 12 of the present invention uses a natural language processing algorithm to process the texts included in the learning outcomes. After tokenization, the tokenized keywords are applied to the sentiment analysis algorithm, and the job competency management unit 13 may function to determine the job suitability of the job seeker based on the sentiment analysis results of the tokenized keywords.

Specifically, sentiment analysis is a technical field that analyzes subjective information such as opinions, emotions, evaluations, and attitudes contained in text through a computer. It largely defines which opinions are contained in which part of a natural language-based sentence and summarizes them. It is accomplished through a process of

As a methodology for sentiment analysis, vocabulary-based sentiment analysis has been previously performed, but with the recent commercialization of machine learning such as artificial intelligence and deep learning, analysis using these models is being conducted. Recently, BERT (Bidirectional Encoder Representations form transformers) has been used. ), many neural network models using transformer-based machine learning are being applied, and in the present invention, at least one of these sentiment analysis methodologies is used to determine whether the emotions revealed in the job seeker's learning outcomes are positive, negative, or neutral. This allows it to function to determine job suitability of job seekers.

On the other hand, in another preferred embodiment of the present invention, the impression of learning about the learning data already performed by the job seeker terminal 20 is stored as a recording area in the input interface provided to the job seeker terminal 20 for creating the above-described learning outcomes. The recording area to be recorded is further allocated (see 100 in FIG. 3), and the recording area where learning impressions are recorded is divided into the recording area where the most accomplished and least accomplished learning contents are recorded, and the learning outcome analysis unit (12) Tokenize the texts written in the recording area corresponding to the most accomplished learning content and the texts written in the recording area corresponding to the unaccomplished learning content through a natural language processing algorithm, and each tokenized keyword It may function to assign weight to the job competency of each job seeker managed by the job competency management department 13 by identifying the job competency corresponding to the job competency.

As an example, referring to 200 in FIG. 4, the learning outcome that the method of writing a watch repair request form was achieved as the most accomplished content in the learning outcomes created from the job seeker terminal 20 was recorded, and the content that was not achieved or When the learning outcome that there was no difficult content is recorded, the job competency management unit 13 of the present invention assigns a weight such that the weight of the job seeker's technical competency, which is the job competency corresponding to the watch repair request, is increased by, for example, 10%. It can be done.

Of course, in the embodiment 200 of FIG. 4, it was recorded that there was no content that could not be achieved or difficult content, but, for example, a record was input that it was difficult to memorize how to indicate a problem in a watch repair request form from the job seeker terminal 20. Assuming that this is the case, the job competency management unit 13 of the present invention reduces the weight of the job seeker's knowledge competency, which is the job competency corresponding to the method of indicating a problem in a watch repair request, by 10%, so that the job seeker's individual job Capacity management may be implemented, but the present invention is not limited thereto.

In other words, in the present invention, by performing the above functions, the effect of systematically managing the job seeker's personal job competency based on the learning outcomes entered by the job seeker can be expected.

Meanwhile, referring to FIG. 2 as another embodiment of the present invention, in the present invention, the main components of the learning activity record-based job competency information provision system 10, including job seeker job competency acquisition descriptions for each job in the luxury watch and jewelry industry, are as described above. It may further include a result report generation unit (14) along with a learning outcome creation request unit (11), a learning outcome analysis unit (12), and a job competency management unit (13).

Specifically, the above-mentioned result report generation unit 14 performs the function of the above-described learning outcome analysis unit 12, and analyzes the results of analyzing a plurality of learning outcomes created in the subscriber terminal during a preset critical period to determine the job seeker's individual status. It functions to generate a report on the results of job competencies.

At this time, the result report on the job competency of the individual job seeker generated by the above-mentioned result report generation unit 14 is transmitted to the hiring entity terminal via the cloud server-based matching server 30 provided to match the hiring entity and the job seeker. (40) (e.g., the concept of a terminal that includes at least one of a company or an institution).

As an embodiment, the hiring entity terminal 40 connects to the matching server 30, inputs required talent information (for example, job-related information), and then selects a preset number of people who match the inputted talent information. Job seeker information can be provided and viewed, and among them, information on job seekers registered as interested personnel by the hiring entity terminal 40 can be provided and viewed as a result report.

Specifically, the result report related to the job seeker's job competency provided to the hiring entity terminal 40 may include a word cloud visualized using one or more keywords extracted from a plurality of learning outcomes created in the job seeker terminal 20.

At this time, one word cloud may be created for all of the above-mentioned job performance requirements, but preferably, as shown at 400 in FIG. 5, a plurality of word clouds are created for each job performance requirement (attitude, knowledge, technology, or equipment). It is desirable to create a report so that when the hiring entity receives a report on the results of the job seeker, it is desirable to be able to intuitively understand and see what job competencies the job seeker has for each job performance requirement just by looking at the word cloud. do.

Meanwhile, each keyword constituting the above-mentioned word cloud should include keywords extracted from the learning outcomes written by the job seeker, but the format set for the keywords can be differentiated according to the job competency of the individual job seeker.

As an example, the plurality of keywords constituting the word cloud are composed of main keywords extracted from the learning outcomes of the job seeker, and the keywords with high frequency in the learning outcomes written by the job seeker are highlighted in a format (for example, the size of the keyword is changed to another keyword). You can set it larger than others, display the keyword color as an accent color, etc.).

At this time, the higher the frequency of keywords, the more emphasis format is applied. It is natural for job seekers to focus their learning on learning data in a specific field, so that specific keywords appear repeatedly, and it is expected that job competency in that specific field will improve. It can be understood that this is because it can be seen.

In addition, as another example, the plurality of keywords constituting the word cloud are composed of main keywords extracted from the job seeker's learning achievements, and are included in the keywords written in the record area where the record of the most accomplished contents is entered among the learning achievements record area. By applying an emphasis format, the job seeker may be able to appeal to the hiring entity about his/her job capabilities, but the present invention is not limited to this.

In addition, the result report generation unit 14 of the present invention allows individual viewing of a plurality of learning outcomes created in the job seeker terminal 20. However, since it takes a considerable amount of time to browse and examine a plurality of learning outcomes one by one at the hiring entity terminal 40, in the present invention, a request for generating a summary of a plurality of learning outcomes can be received from the hiring entity terminal 40. .

Accordingly, the result report providing unit of the present invention summarizes a plurality of sentences included in the plurality of learning outcomes from the hiring entity terminal 40 into a preset number of sentences and provides a summary of the plurality of learning outcomes to the hiring entity terminal 40. It can function to provide.

Continuing a more detailed description with reference to 500 in FIG. 6, in the present invention, as shown in 500 in FIG. 6, the LDA (Latent Dirichlet Allocation) algorithm is used to briefly process a plurality of learning outcomes created on the job seeker terminal 20. can be used.

This LDA algorithm can be understood as an algorithm that estimates the distribution of words by topic in a given plurality of learning outcomes, analyzes the distribution of words found in a given document, and observes what topics the plurality of learning outcomes cover. there is.

The LDA algorithm described in more detail assigns random topic numbers to all words in the learning output, then calculates the distribution of topics within the learning output and the distribution of words within the learning output to identify key topics related to the job competency of the individual job seeker in the learning output. It is often assumed that

Of course, in another embodiment of the present invention, words with a high correlation coefficient are extracted from sentences in which words corresponding to the keyword set appear using a co-occurrence word analysis or co-occurrence analysis algorithm instead of the LDA algorithm described above. , an algorithm may be used to estimate key topics related to job competencies from learning outcomes, but the present invention is not limited thereto.

In addition, in the present invention, if major topics related to the job capabilities of individual subscribers are estimated from a plurality of learning outcomes using an algorithm including at least one of the LDA algorithm and the co-occurring word analysis algorithm described above, the present invention provides the extracted words Information about the distribution and location of words is applied to a natural language processing algorithm to learn the structure of sentences in which words appear, and to generate sentences condensed to sentences within a preset number (for example, sentences within 5).

At this time, in the present invention, the frequency of use of auxiliaries and adverbs can be weighted so that sentences containing words that are judged to be of high importance due to the large distribution of words can be highlighted, and for more natural sentence processing, for example, RNN (Recurrent It is possible to increase the readability of short text content by using a natural language processing algorithm such as a Neural Network language model, but the present invention is not limited to this.

On the other hand, although not explicitly mentioned in the attached drawing, the hiring entity terminal 30, which has received the job seeker's result report, proposes employment to one or more job seeker terminals 20 who wish to be hired or interview. Alternatively, it is possible to transmit a message about an interview offer, so that when the job seeker terminal 20 that has received the above message responds to the recruitment or interview offer, the job seeker terminal 20 and the hiring entity terminal 30 can communicate with each other. By providing a separate interface, it is possible to facilitate a meeting between a job seeker and an employer, but the present invention is not limited thereto.

In general, according to the system for providing job competency information based on learning activity records including job competency acquisition descriptions for each job in the luxury watch and jewelry industry described above, in the present invention, when learning data is performed on the job seeker terminal, the learning outcomes are provided to the job seeker terminal. By repeating the process of determining the job seeker's learning performance, such as requesting writing, it has the effect of making it possible to manage job competency based on the job seeker's learning activities.

In addition, according to an embodiment of the present invention, in the present invention, the job seeker's learning performance is evaluated by analyzing the learning outcomes created on the job seeker's terminal, and the job suitability of the job seeker can be determined, thereby matching the hiring entity and the job seeker. This has the effect of increasing the city matching success rate.

In addition, according to an embodiment of the present invention, in providing the job seeker's job competency information managed based on learning outcomes to the hiring entity seeking a job, the job seeker's job competency information is provided using a word cloud. By providing it in a more intuitive form, it can be expected to have the effect of enabling employers to hire the talent they need more quickly.

As described above, although the embodiments have been described with limited examples and drawings, various modifications and variations can be made by those skilled in the art from the above description.

Next, referring to FIG. 7, FIG. 7 illustrates an example of the internal configuration of a computing device according to an embodiment of the present invention, and in the following description, overlapping with the description of FIGS. 1 to 6 described above Description of unnecessary embodiments will be omitted.

As shown in FIG. 7, the computing device 10000 includes at least one processor 11100, a memory 11200, a peripheral interface 11300, and an input/output subsystem ( It may include at least an I/O subsystem (11400), a power circuit (11500), and a communication circuit (11600). At this time, the computing device 10000 may correspond to a user terminal (A) connected to a tactile interface device or the computing device (B) described above.

The memory 11200 may include, for example, high-speed random access memory, magnetic disk, SRAM, DRAM, ROM, flash memory, or non-volatile memory. there is. The memory 11200 may include software modules, instruction sets, or various other data necessary for the operation of the computing device 10000.

At this time, access to the memory 11200 from other components such as the processor 11100 or the peripheral device interface 11300 may be controlled by the processor 11100.

The peripheral interface 11300 may couple input and/or output peripherals of the computing device 10000 to the processor 11100 and the memory 11200. The processor 11100 may execute a software module or set of instructions stored in the memory 11200 to perform various functions for the computing device 10000 and process data.

The input/output subsystem 11400 can couple various input/output peripheral devices to the peripheral interface 11300. For example, the input/output subsystem 11400 may include a controller for coupling peripheral devices such as a monitor, keyboard, mouse, printer, or, if necessary, a touch screen or sensor to the peripheral device interface 11300. According to another aspect, input/output peripheral devices may be coupled to the peripheral interface 11300 without going through the input/output subsystem 11400.

Power circuit 11500 may supply power to all or some of the terminal's components. For example, power circuit 11500 may include a power management system, one or more power sources such as batteries or alternating current (AC), a charging system, a power failure detection circuit, a power converter or inverter, a power status indicator, or a power source. It may contain arbitrary other components for creation, management, and distribution.

The communication circuit 11600 may enable communication with another computing device using at least one external port.

Alternatively, as described above, if necessary, the communication circuit 11600 may include an RF circuit to transmit and receive RF signals, also known as electromagnetic signals, to enable communication with other computing devices.

This embodiment of FIG. 7 is only an example of the computing device 10000, and the computing device 11000 omits some components shown in FIG. 7, further includes additional components not shown in FIG. 7, or 2 It may have a configuration or arrangement that combines more than one component. For example, a computing device for a communication terminal in a mobile environment may further include a touch screen or a sensor in addition to the components shown in FIG. 7, and may include various communication methods (WiFi, 3G, LTE) in the communication circuit 1160. , Bluetooth, NFC, Zigbee, etc.) may also include a circuit for RF communication. Components that may be included in the computing device 10000 may be implemented as hardware, software, or a combination of both hardware and software, including one or more signal processing or application-specific integrated circuits.

Methods according to embodiments of the present invention may be implemented in the form of program instructions that can be executed through various computing devices and recorded on a computer-readable medium. In particular, the program according to this embodiment may be composed of a PC-based program or a mobile terminal-specific application. The application to which the present invention is applied can be installed on a user terminal through a file provided by a file distribution system. As an example, the file distribution system may include a file transmission unit (not shown) that transmits the file according to a request from the user terminal.

The device described above may be implemented with hardware components, software components, and/or a combination of hardware components and software components. For example, devices and components described in embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), It may be implemented using one or more general-purpose or special-purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. A processing device may execute an operating system (OS) and one or more software applications that run on the operating system.

Additionally, a processing device may access, store, manipulate, process, and generate data in response to the execution of software. For ease of understanding, a single processing device may be described as being used; however, those skilled in the art will understand that a processing device may include multiple processing elements and/or multiple types of processing elements. It can be seen that it may include. For example, a processing device may include a plurality of processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are possible.

Software may include a computer program, code, instructions, or a combination of one or more of these, which may configure a processing unit to operate as desired, or may be processed independently or collectively. You can command the device. Software and/or data may be used by any type of machine, component, physical device, virtual equipment, computer storage medium or device to be interpreted by or to provide instructions or data to a processing device. It can be embodied permanently or temporarily. Software may be distributed over networked computing devices and stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., singly or in combination. Program instructions recorded on the medium may be specially designed and configured for the embodiment or may be known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -Includes optical media (magneto-optical media) and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, etc.

Examples of program instructions include machine language code, such as that produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

As described above, although the embodiments have been described with limited examples and drawings, various modifications and variations can be made by those skilled in the art from the above description. For example, the described techniques are performed in a different order than the described method, and/or components of the described system, structure, device, circuit, etc. are combined or combined in a different form than the described method, or other components are used. Alternatively, appropriate results may be achieved even if substituted or substituted by an equivalent. Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims described below.

Claims (10)

In the system for providing job competency information based on learning activity records, including job competency acquisition descriptions for job seekers in the luxury watch and jewelry industry, implemented in a computing device including one or more processors and one or more memories that store instructions executable by the processor, comprising:
A learning product creation request unit that requests the job seeker terminal, who has performed learning using the learning data provided to improve job competency, to create a learning outcome for the already performed learning data;
A learning outcome analysis unit that electronically documents learning outcomes written in natural language on the job seeker's terminal in accordance with the function of the learning outcome creation request unit, and analyzes the electronically documented learning outcomes based on artificial intelligence technology including at least a natural language processing algorithm; and,
By receiving the analysis results of the learning outcomes from the learning outcome analysis unit, evaluating the job seeker's learning performance with respect to the learning data, and updating the job seeker's individual job competency based on the evaluated learning performance, the job seeker Includes a job competency management department that ensures that individual job competencies are managed;
The learning outcome request section is:
Immediately after learning of the learning data is completed at the job seeker terminal and after a preset threshold time has elapsed from the time when learning of the learning data is completed, an input interface for requesting creation of the learning outcome is provided to the job seeker terminal. Ensure that two or more learning outcomes are created for the training data,
The learning data is,
Include learning about attitudes, knowledge, skills and equipment required to perform the job;
In the input interface provided to the job seeker terminal for creating the learning outcomes, respective recording areas for attitudes, knowledge, skills and equipment that are requirements for performing the job are allocated, allowing the job seeker terminal to record the assigned information. Ensure that detailed learning outcomes for the above job performance requirements are recorded in the area,
The input interface provided to the job seeker terminal for creating the learning outcomes is further allocated a recording area in which impressions of learning about learning data already performed by the job seeker terminal are recorded as the recording area,
The recording area where the learning impressions are recorded is,
It is divided into recording areas where the most accomplished and least accomplished learning content is recorded,
In the learning outcome analysis department,
Texts written in the recording area corresponding to the most accomplished learning content and texts written in the recording area corresponding to the unachieved learning content are tokenized through the natural language processing algorithm, and correspond to each tokenized keyword. By identifying the job competency required, weight is given to the job competency of each job seeker managed by the job competency management department.
If learning outcomes that indicate that there were no content that was not achieved or that were difficult were recorded, the weight value of the job seeker's job competency corresponding to each keyword is increased, and if it is entered that there is content that was not achieved or that was difficult, the weight value for the job competency of the job seeker corresponding to each keyword is increased. Reduce the weight value for the job competency of the corresponding job seeker,
The system for providing job competency information based on learning activity records, including job competency acquisition descriptions for job seekers for each job in the luxury watch and jewelry industry,
It further includes a result report generation unit that generates a result report on the job competency of the individual job seeker based on the results of analyzing a plurality of learning outcomes created on the job seeker terminal during a preset critical period,
The result report on the job competency of the individual job seeker generated in the result report generation unit shall be provided to the terminal of the employer, including at least one of the companies and institutions that have registered the job seeker as a person of interest, and shall be provided with the job seeker's result report. In this hiring entity terminal, a message about a job offer or interview offer can be sent to one or more job seeker terminals who wish to be hired or have an interview, so that the job seeker terminal that has received the message about the job offer or interview offer is Job competency based on learning activity records including job competency acquisition descriptions for each job in the luxury watch and jewelry industry, characterized by providing a separate interface that allows communication between the job seeker's terminal and the hiring entity's terminal when responding to a recruitment or interview offer. Information provision system.
delete According to paragraph 1,
The learning outcome analysis department,
Compared to the first learning outcome, which is a learning outcome recorded immediately after learning of the learning data is completed, the second learning outcome is a learning outcome recorded after a preset threshold time has elapsed from the time learning of the learning data is completed. A system for providing job competency information based on learning activity records, including job competency acquisition descriptions for job seekers for each job in the luxury watch and jewelry industry, which is characterized by setting the analysis weight to be relatively high.
delete According to paragraph 1,
The learning outcome analysis department,
When learning outcomes for the job performance requirements are recorded through the input means of the job seeker terminal, the texts written in each recording area of the learning outcomes are tokenized through a natural language processing algorithm,
The job competency management department evaluates the job seeker's learning performance by comparing the similarity between tokenized keywords and key keywords pre-stored as learning goals in the learning data. Job seeker job competency for each job in the luxury watch and jewelry industry. A system for providing job competency information based on learning activity records including acquired skills.
According to paragraph 1,
The learning outcome analysis department,
When learning outcomes for the job performance requirements are recorded through the input means of the job seeker terminal, the texts included in the learning outcomes are tokenized through the natural language processing algorithm, and then the tokenized keywords are applied to the sentiment analysis algorithm. And
The job competency management department evaluates the job suitability of the job seeker based on the sentiment analysis results of the tokenized keywords. Job competency based on learning activity records including job competency acquisition descriptions of job seekers for each job in the luxury watch and jewelry industry. Information provision system.
delete delete According to paragraph 1,
In the result report provided to the hiring entity terminal,
It includes a word cloud visualized using one or more keywords extracted from a plurality of learning outcomes created on the job seeker terminal,
Multiple word clouds are created for each job performance requirement,
Each keyword constituting the word cloud includes keywords extracted from the learning outcomes, and job competency of job seekers for each job in the luxury watch and jewelry industry, characterized in that the format set for the keywords is differentiated according to the job competency of the individual job seeker. A system for providing job competency information based on learning activity records including acquired skills.
According to paragraph 1,
The result report generation unit,
Individual viewing of multiple learning outcomes created on the job seeker terminal is possible,
When a request for generating a summary of the plurality of learning outcomes is received from the hiring entity terminal,
Luxury characterized by applying a preset text summary algorithm to the plurality of learning outcomes to summarize a plurality of sentences included in the plurality of learning outcomes into a preset number of sentences and providing a summary to the hiring entity terminal. A system for providing job competency information based on learning activity records, including job competency acquisition descriptions for job seekers in the watch and jewelry industry.