DocumentCode :
3253079
Title :
Job recommender systems: A survey
Author :
Siting, Zheng ; Wenxing, Hong ; Ning, Zhang ; Fan, Yang
Author_Institution :
Sch. of Inf. Sci. & Technol., Xiamen Univ., Xiamen, China
fYear :
2012
fDate :
14-17 July 2012
Firstpage :
920
Lastpage :
924
Abstract :
The personalized recommender system is proposed to solve the problem of information overload and widely applied in many domains. The job recommender systems for job recruiting domain have emerged and enjoyed explosive growth in the last decades. User profiles and recommendation technologies in the job recommender system have gained attention and investigated in academia and implemented for some application cases in industries. In this paper, we introduce some basic concepts of user profile and some common recommendation technologies based on the existing research. Finally, we survey some typical job recommender systems which have been achieved and have a general comprehension of job recommender systems.
Keywords :
collaborative filtering; personal information systems; recommender systems; recruitment; information overload; job recommender systems; job recruiting domain; personalized recommender system; user profiles; Collaboration; Data mining; Feature extraction; Hidden Markov models; Recommender systems; Resumes; job matching; job recommender system; recommendation technology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science & Education (ICCSE), 2012 7th International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-0241-8
Type :
conf
DOI :
10.1109/ICCSE.2012.6295216
Filename :
6295216
Link To Document :
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