• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.223-229
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• 2022

LinkedIn is one of the most job hunting and career-growing applications in the world. There are a lot of opportunities and jobs available on LinkedIn. According to statistics, LinkedIn has 738M+ members. 14M+ open jobs on LinkedIn and 55M+ Companies listed on this mega-connected application. A lot of vacancies are available daily. LinkedIn data has been used for the research work carried out in this paper. This in turn can significantly tackle the challenges faced by LinkedIn and other job posting applications to improve the levels of jobs available in the industry. This research introduces Text Processing in natural language processing on datasets of LinkedIn which aims to find out the jobs that appear most in a month or/and year. Therefore, the large data became renewed into the required or needful source. This study thus uses Multinomial Naïve Bayes and Linear Support Vector Machine learning algorithms for text classification and developed a trained multilingual dataset. The results indicate the most needed job vacancies in any field. This will help students, job seekers, and entrepreneurs with their career decisions

• Culinary science and hospitality research
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• v.12 no.3 s.30
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• pp.91-107
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• 2006

This thesis aims to consider theories of job information on foodstylist, conduct a survey among culinary arts science high school students who are in the most critical period of decision-making for the future career, and analyse the survey results on foodstylist by using SPSS10.0. The analysis shows that culinary high school students mainly get their job information on foodstylist through mass media. Thus, it can be deduced that use of mass media and the Internet can be the most effective to promote the awareness level of foodstylist. Culinary high schoolers' parents were positive about female students' being foodstylists, and those going to college showed more interest than job seekers about being foodstylists. In addition, the result of Bonferroni post-hoc test according to parents' monthly income showed that those with higher monthly income were positive about their children's being foodstylists. However, given that culinary high schoolers' overall satisfaction is low, provision of the information through a variety of information channels is necessary. It is expected that promotion of the information provision will serve a turning point in awareness.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.351-368
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• 2021

This paper is meaningful in that it empirically studies the good job condition of which young people think and the impact of job search behavior on employment. In addition, employment status and additional job search performance were set as performance variables. The main research results of this study are as follows. First, as for the good job condition considered by young people, wages and salaries in terms of companies, job stability in terms of environment, and work-life balance in terms of individuals were found. Second, job search behavior was found to be a key variable influencing employment status and job search performance. Third, it was found that job-search stress injures employment. Finally, work experience promotes employment and job search performance. Therefore, to increase the employment success rate of young people, above all, various supports for increasing the frequency of young job seekers' active job search behavior are needed. To this end, it suggests that it is necessary to develop a customized youth policy service model and to provide systematic services to meet the needs of young people.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.602-604
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• 2017

구직자는 취업을 하기 위해 다양한 채용 공고를 확인하고 이력서를 제출하는데 많은 시간을 소비한다. 만약 채용 추천 시스템을 통해 사용자에게 알맞는 회사를 추천해 준다면 구직자는 구직 활동 시간을 절약할 수 있다. 이를 위해 본 논문에서는 구직자에게 알맞는 회사를 추천하기 위한 알고리즘을 알아본다.

• 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 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.

• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.183-188
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• 2018

This paper examines career self-help advice in light of its influence on white-collar job searching in the US. After a brief overview of the white-collar labor market changes in the past few decades and the rise of the career self-help industry in America, it focuses on career self-help advice concerning a resume and networking that involves the use of information communication technology (ICT) through the review of career self-help manuals and other related literature. Finally, it looks at some of its major limits, especially the problem of presenting job searching in terms of individual efforts without regard to its structural aspects and its implications - individual responsibility for job searching and its outcomes - along with a suggestion for the type of help that can be offered to job seekers.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.125-131
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• 2023

This study is a descriptive research study to identify the social support, depression, self-control, and employment stress levels of job seekers and to identify their correlation and influencing factors. The subjects of the study scored 4.13 points for social support, 0.79 points for depression, 3.10 points for self-control and 2.15 points for employment stress. The results of analyzing employment stress according to the general characteristics of the subjects showed that there was no statistically significant difference in gender, and there were significant differences in age, grade, major, and grades. Employment stress of the subjects is employment stress-depression (r=.625, p=).001), employment stress - self-control (r=.251, p=.001) and employment stress - social support (r=-, 519, p=).001) showed a negative correlation. Depression is depression-social control (r=.300, p=).001) shows a static correlation and depression-social support (r=-.503, p=).001) shows a negative correlation. Social support was not correlated with social support-self-control (r=-.059, p=414). Social support and depression were the factors affecting employment stress. We would like to provide basic data on programs and education to reduce the employment stress of college students.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.224-231
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• 2018

Recently, the importance of intelligent personalized services is increasing in the era of the 4th Industrial Revolution. In this paper, we proposes design and implementation of the agent recruitment service system for the intelligent headhunting service. The proposed service system has designed and implemented an intelligent service system to efficiently recruit and manage applicants(job seekers). In addition, we develops the modules that can analyze the profile information of the applicant(job seeker), and implement the algorithm to predict the talent verification and analyze the talent type. The proposed service system is expected to contribute to designing the innovative and new service models for the intelligent agent recruitment service system.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.3
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• pp.248-259
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• 2009

This paper analyzes the interactions among regional labor markets in Korea. Specifically, we focus on the job market externality between neighboring regions. To estimate the job matching functions, we construct panel data on unemployment, vacancies and hires for the period of January 2004 through December 2007 for 15 cities and provinces in Korea. We employ various spatial econometric techniques to avoid the problem of spatial autocorrelation which frequently arises when dealing with regional data. Main findings are as follows. First, estimation results are consistent with conventional job matching theory. That is, as the number of job searchers and vacancies increase, the number of hires also rises. And it is relatively easier for firms to hire workers than for job seekers to find jobs. Second, it is found that, other things equal, the possibility of job matching is higher in large metropolitan areas than rural areas. Finally, the findings show that the number of job searchers in neighboring areas is negatively correlated with the number of hires in the area. Likewise, the number of vacancies in neighboring areas is positively correlated with number of hires in the area. These provide clear evidence on the existence of regional spillover effects.