• 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