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