• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.86-95
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• 2022

Online recruitment websites discuss job demands in various fields, and job postings contain detailed job specifications. Analyzing this text can elucidate the features that determine job salaries. Text embedding models can learn the contextual information in a text, and explainable artificial intelligence frameworks can be used to examine in detail how text features contribute to the models' outputs. We collected 733,625 job postings using the WORKNET API and classified them into low, mid, and high-range salary groups. A text embedding model that predicts job salaries based on the text in job postings was trained with the collected data. Then, we applied the SHapley Additive exPlanations (SHAP) framework to the trained model and discovered the significant words that determine each salary class. Several limitations and remaining words are also discussed.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.201-228
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• 2023

This study was conducted to analyze the trends of librarian job recruitment in Korea and overseas. A total of 489 librarian job postings posted on the internet portal site "Saseo e-Ma-eul" were collected for the Korean data, and 6,600 data were collected from "ALAJobList" for the international data. The research period spans from January 2020 to August 2022. The data were subjected to regional distribution analysis, frequency analysis, and topic modeling. As a result of the study, the number of Korean librarian job postings was the highest in Seoul with 280, while California was the state with the highest number of job postings overseas with 662. According to the frequency analysis, the main task of Korean data is 'management' 23.42%, and the core competency is 'certificate' 16.61%. For overseas data, 'Library Service' is the main task of 8.72%, and 'Communication Skills' is the most important core competency of 10.13%. In topic modeling, five topics were identified for each area 4 in total, including Korean and international job description and requirements. The analysis results confirm that the duties and qualifications derived from Korean and international job postings for librarians are related to the core competencies proposed by major library associations such as the American Library Association (ALA) and the Korean Library Association.

• Journal of the Korea Fashion and Costume Design Association
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• v.22 no.3
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• pp.75-87
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• 2020

As the online industry is vitalized by the fashion market, there is a tendency to believe that the recruitment of manpower in the online distribution field is increasing. Thus, this study attempts to analyze the job types and job functions for recruitment in the fashion industry based on job search sites and based on this, suggest an educational direction within the department of fashion design. First, when examining the size (number of employees) of fashion companies that posted jobs, the fashion companies with 30 or fewer employees accounted for 60.7% of the postings, and the location of the fashion companies was most commonly in Seoul with 144 companies located in Gangnam (Seocho-gu, Gangnam-gu). As for the recruitment conditions of the fashion companies, "academic level-irrelevant" was the highest with 42.6%, and in terms of gender and age, 59.3% of the cases were marked as "gender and/or age-irrelevant". Examining the types of jobs for recruitment in the fashion industry, fashion designers were the most popular at 52.6%, followed by on and off-line companies' MD, VMD, and stylist in that order. In the results of examining job function change, it is thought that the fashion design department should have basic educationon in that respect.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.247-264
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• 2016

With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

• Smart Media Journal
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• v.12 no.2
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• pp.36-41
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• 2023

With the advent of applicant tracking systems, online recruitment has become more popular, and recruitment fraud has become a serious problem. This research aims to develop a reliable model to detect recruitment fraud in online recruitment environments to reduce cost losses and enhance privacy. The main contribution of this paper is to provide an automated methodology that leverages insights gained from exploratory analysis of data to distinguish which job postings are fraudulent and which are legitimate. Using EMSCAD, a recruitment fraud dataset provided by Kaggle, we trained and evaluated various single-classifier and ensemble-classifier-based machine learning models, and found that the ensemble classifier, the random forest classifier, performed best with an accuracy of 98.67% and an F1 score of 0.81.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.285-288
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• 2018

데이터 정형화기술은 자연어 처리 및 인공지능분야, 데이터베이스 등 다양한 분야에서 중요한 핵심적인 기술 중 하나이다. 최근 정형화 문제를 푸는 많은 신경망 기반 알고리즘들이 제안되었으나, 기존의 모든 알고리즘이 키워드의 후보가 입력으로 주어진다고 가정하고 있으며, 알고리즘 대부분은 두 개의 속성(attribute)을 가지는 이진 관계(binary relation)만 처리할 수 있다는 한계가 있다. 본 논문에서는 컨볼루션 신경망을 이용한 N항 관계 정형화 방업을 제안하고, 이를 이용한 구인 광고 정형화 시스템을 개발하고 성능을 평가한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.430-431
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• 2023

본 논문에서는 GPT-4 기반의 채용공고별 AI 자소서 작성 가이드 개인화 서비스를 제안한다. 이 서비스는 지원자들에게 시간 절약과 효율적으로 작성된 글을 제공하며, 기업의 요구사항과 지원자의 역량을 최대한 반영한 경쟁력 있는 자기소개서를 작성할 수 있다. 본 연구는 기존의 템플릿 기반 글 작성 서비스의 한계를 극복하고, 인공지능 기반의 GPT-4 를 활용하여 개인화된 글 작성을 가능하게 한다. 시스템 구현을 통해 최적화된 프롬프트를 연구하며, 이 방법론은 자기소개서 외 다양한 분야의 글 작성에도 활용될 수 있다. 이 서비스의 활용으로 지원자들의 경쟁력이 높아지고, 기업들은 더 적합한 인재를 찾는 데 도움을 받을 수 있을 것으로 기대된다.

• Information Systems Review
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• v.25 no.3
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• pp.179-197
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• 2023

As a sufficient workforce supports the industry's growth, workforce training has also been carried out as part of the industry promotion policy. However, the market still has a shortage of skilled mid-level workers. The information security disclosure requires organizations to secure personnel responsible for information security work. Still, the division between information technology work and job areas is unclear, and the pay is not high for responsibility. This paper compares job keywords in advertisements for the information security workforce for 2014, 2019, and 2022. There is no difference in the keywords describing the job duties of information security personnel in the three years, such as implementation, operation, technical support, network, and security solution. To identify the actual needs of companies, we also analyzed and compared the contents of job advertisements posted on online recruitment sites with information security sector knowledge and skills defined by the National Competence Standards used for comprehensive vocational training. It was found that technical skills such as technology development, network, and operating system are preferred in the actual workplace. In contrast, managerial skills such as the legal system and certification systems are prioritized in vocational training.

• Informatization Policy
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• v.28 no.2
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• pp.34-56
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• 2021

According to the Fourth Industrial Revolution, demand for and interest in jobs in the field of AI and data science - such as artificial intelligence/data analysts - are increasing. In order to keep pace with this trend, and to supply human resources that can effectively perform such jobs in the relevant fields in a timely manner, job seekers must develop the competencies required by the companies, and universities must be in charge of training. However, it is difficult to devise appropriate response strategies at the level of job seekers, companies and universities, which are stakeholders in terms of supplying suitably competent personnel. Therefore, the purpose of this study is to determine which competencies are required in practice in order to cultivate and supply human talents equipped with the necessary job competencies, and to propose plans for the development of the required competencies at the university level. In order to identify the required competencies in the field of AI and data science, data on job postings on the LinkedIn site, the recruitment platform, were analyzed using text mining techniques. Then, research was conducted with the aim of devising and proposing concrete plans for competency development at the university level by comparing and verifying the results of the international graduate school curriculum in the field of AI and data science, and the interview results with the hiring managers, respectively, with the results of the topic model.

• Journal of Convergence for Information Technology
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• v.10 no.9
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• pp.237-243
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• 2020

This study examines the inequality of female golf leaders in recruitment and promotion and investigates alternatives to overcome them. It consisted of in-depth interviews and observations of the participants of this researcher by 9 female golf instructors who were employed in the driving range and had more than 10 years of teaching experience. Area analysis and classification analysis were used, and expert consultation, triangulation verification, and reconfirmation with participants were performed. The results first, Female golf leaders were unable to compete equally in the network of male golf leaders who advanced first. Second, female golf leaders were faithful to the role theory of women who have been educated in Confucian culture in Korean society. Third, to overcome the gender inequality reality, education was selected and self-esteem was raised through education. Fourth, fair opportunities should be given through job postings and job standardization. Lastly, it was confirmed that the proportion of athletes soon leads to the proportion of leaders, and that the number of leaders becomes a condition for equality.