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Graduates Profile Mapping based on Job Vacancy Information Clustering

机译:基于职位空缺信息聚类的毕业生剖面映射

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Nowadays, an industry’s expectation that’s often not fulfilled by job applicants require companies to actively cooperate with universities, one of the reasons is through employees that is considered to have good performance to find talents within their alma mater. This research aims to analyze job vacancy information uploaded by graduates for juniors in their university that can be mapped into a graduate’s profile and evaluation materials in making a curriculum. Collected job vacancy information from several communication media are generally unstructured data which requires it to be preprocessed first through a data mining convention to produce several terms ready to be processed, continued with implementation of TF-IDF, feature extraction using PCA, and grouping using k-Means algorithm. The clustering analysis found 3 job clusters i.e. developer, teacher and researcher/lecturer as job vacancies that frequently shared by graduates. This result obtained from clustering analysis using 10 words as a minimum document frequency based on Elbow Method and Silhouette Coefficient analysis.
机译:如今,这往往不是由求职者实现一个行业的预期要求企业积极与高校合作,原因之一是通过被认为具有良好的性能,找到自己的母校内人才的员工。本研究旨在分析由毕业生在他们的大学大三学生,可以在制作课程被映射到一个毕业生的个人资料和评估材料上传的职位空缺信息。从多种通信媒体收集到的职位空缺信息一般都是非结构化数据,要求予以通过数据挖掘大会产生几个方面准备处理后的第一预处理,继续使用PCA,实现TF-IDF,特征提取,并用k分组-Means算法。聚类分析发现3分作业簇即显影剂,教师和研究人员/讲师作为经常由毕业生共享职位空缺。该结果从聚类分析使用10个字作为基于弯头的方法和剪影系数分析的最小文档频率获得的。

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