基于LinkedIn技能背书的协同过滤信息技术职位推荐系统

IF 0.4 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS African Journal of Information Systems Pub Date : 2020-02-02 DOI:10.24167/SISFORMA.V6I2.2240
Latifah Diah Kumalasari, A. Susanto
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引用次数: 11

摘要

信息工程专业毕业的学生在信息技术工作领域有广泛的就业机会,如数据库管理员、数据科学家、UI设计师、IT项目经理、网络工程师、系统分析师、软件工程师和UX设计师。信息技术领域的各个岗位对工作领域的兴趣有不同的技能要求。因此,需要对信息技术技能进行分类,找出适合信息工程专业学生的职业推荐。来自IT专业人士的数据,这些数据来自于IT专业人士的LinkedIn账户,将作为学生的参考。使用K-Means聚类算法对数据进行处理,找出如何使用IT专业人员的数据作为参考的可行性。然后,利用K-NN算法的协同过滤方法,根据学生技能与信息技术工作领域的接近程度确定分类;输出是对信息技术学生技能进行计算后产生的信息技术工作领域推荐。结果通过测试一个被标记为软件工程师的用户作为软件工程师产生推荐输出来测试。
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Recommendation System of Information Technology Jobs using Collaborative Filtering Method Based on LinkedIn Skills Endorsement
Students who are graduated from Informatics Engineering have wide employment opportunities in the information technology work field, such as database administrator, data scientist, UI designer, IT project manager, network engineer, system analyst, software engineer and UX designer. Each job in I nformation T echnology field has different skill requirement for the interest of work field. Therefore, IT skill classification is needed to find out the suitable career recommendation for Informatics Engineering students. Data from IT professionals which are obtained from LinkedIn account of IT professionals will be processed as reference for students. Data are processed using K-Means Clustering algorithm to find out how is feasible IT professionals data are used as a reference. Then, Collaborative Filtering method by the K-NN algorithm is used to determine classification based on the proximity between student skills and information technology job field. The output is recommendation of information technology job field which are generated from calculate of IT student skills. Result has been tested by testing one of user that has been labeled software engineer produce a recommendation output as a software engineer.
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来源期刊
African Journal of Information Systems
African Journal of Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
14.30%
发文量
0
审稿时长
30 weeks
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