Hyred HYbrid Job REcommenDation System

被引：0
|
作者：
Coelho, Bruno [1 ]
Costa, Fernando [2 ]
Goncalves, Gil M. [1 ,3 ]
机构：
[1] Ctr Inovacao Matosinhos, INOVA, Rua Dr Afonso Cordeiro 567, P-4450309 Matosinhos, Portugal
[2] Super Inst Engn Porto, Dept Informat Engn, P-4249015 Porto, Portugal
[3] Univ Porto, Fac Engn, Dept Informat Engn, P-4200465 Porto, Portugal
来源：
2015 12TH INTERNATIONAL JOINT CONFERENCE ON E-BUSINESS AND TELECOMMUNICATIONS (ICETE), VOL 2 | 2015年
关键词：
Recommender Systems; Decision Support Systems; Match-making Algorithms; Jobs; Employment; Work; Teams; User Modelling; Content-based Filtering; Collaborative Filtering;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
Nowadays people search job opportunities or candidates mainly online, where several websites for this purpose already do exist (LinkedIn, Guru and oDesk, amongst others). This task is especially difficult because of the large number of items to look for and manual compatibility verification. What we propose in this paper is a Hybrid Job Recommendation System that considers the user model (content-based filtering) and social interactions (collaborative filtering) to improve the quality of its recommendations. Our solution is also able to generate adequate teams for a given job opportunity, based not only on the needed competences but also on the social compatibility between their members.
引用
收藏
页码：29 / 38
页数：10
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