A novel asymmetric semantic similarity measurement for semantic job matching

Bo Zhu*, Xin Li, Jesus Bobadilla Sancho

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

3 引用 (Scopus)

摘要

Applying semantic similarity techniques in semantic matching applications can help to match information not only lexically but also semantically. In this paper, we extend the conventional semantic similarity measures for retrieving and ranking employment candidates in the case of semantic job matching. A framework for calculating asymmetric conceptual skill similarity is proposed, and validated in a use case of programming job matching. Within this case, a specific skills taxonomy has been formalized in Simple Knowledge Organization System (SKOS). A novel asymmetric semantic similarity measurement based on weighted-path-counting is proposed and validated in the use case. The proposed algorithms are evaluated by comparing them to user ranks, and our experimental results show that the proposed algorithms have better performance in ranking comparing to the conventional algorithms.

源语言英语
主期刊名2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
出版商Institute of Electrical and Electronics Engineers Inc.
152-157
页数6
ISBN(电子版)9781538630167
DOI
出版状态已出版 - 2 7月 2017
活动2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017 - Shenzhen, 中国
期限: 15 12月 201717 12月 2017

出版系列

姓名2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
2018-January

会议

会议2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
国家/地区中国
Shenzhen
时期15/12/1717/12/17

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