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A Personalized Job Recommended System Using Hybrid Collaborative Filtering Algorithm

Author

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  • N. Rajganesh
  • S. Seetha Devi
  • J. Keerthana
  • R. Poovizhi

Abstract

Job recommendation systems usually involve exploiting the relations among known features and content that describe jobs. Implement the interface with personalization and profile based search for job recommendations. Construct the user profiles based on job type, interest, location and date. Combine content and collaborative filtering approach to recommend the jobs with improved accuracy rate. The two traditional recommendation techniques are content-based and collaborative filtering. While both methods have their advantages, they also have certain disadvantages, some of which can be solved by combining both techniques to improve the quality of the recommendation. The resulting system is known as hybrid collaborative filtering.

Suggested Citation

  • N. Rajganesh & S. Seetha Devi & J. Keerthana & R. Poovizhi, 2018. "A Personalized Job Recommended System Using Hybrid Collaborative Filtering Algorithm," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 3(3), pages 191-196, April.
    • Handle: RePEc:jbh:ijsrcs:v3:y2018:i3:id:hcseit183350
    Note: Article URL: https://ijsrcseit.com/CSEIT183350
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