• Title/Summary/Keyword: KOCM

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중국 인터넷 소설의 한국어 번역 양상 - KOCM 출판사의 《펫 마스터》를 중심으로

  • Choe, Jae-Yong
    • 중국학논총
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    • no.63
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    • pp.137-159
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    • 2019
  • In this paper, I tried to analyse the recent trend of Korean translation of Chinese novels. I categorized the korean translation into several types, and tried to reveal the meaning of the "Hiding of Chinese element" phenomenon that has recently emerged in the translation of Internet novels. KOCM has been translating quite a fewChinese Internet novels. One of the publisher's translations, , which has gained considerable popularity in Korea, will be a focus of the analysis. The localization strategy of is quite damaging to the original work. At the same time, however, it also makes it easier for readers to consume novels without experiencing cultural discounts. Therefore, could be considered as a experiment to overcome the cultural gap between the two countries.

Job Preference Analysis and Job Matching System Development for the Middle Aged Class (중장년층 일자리 요구사항 분석 및 인력 고용 매칭 시스템 개발)

  • Kim, Seongchan;Jang, Jincheul;Kim, Seong Jung;Chin, Hyojin;Yi, Mun Yong
    • 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.