A Personalized Job Recommended System Using Hybrid Collaborative Filtering Algorithm

Authors(4) :-N. Rajganesh, S. Seetha Devi, J. Keerthana, R. Poovizhi

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.

Authors and Affiliations

N. Rajganesh
Assitant Professor, Department of Information Technology,A.V.C College of Engineering, Tamil Nadu, India
S. Seetha Devi
UG Student, Department of Information Technology, A.V.C College of Engineering, Tamil Nadu, India
J. Keerthana
UG Student, Department of Information Technology, A.V.C College of Engineering, Tamil Nadu, India
R. Poovizhi

Job Recommender, Information Retrieval,Semantic Matching,Person Similarities.

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Publication Details

Published in : Volume 3 | Issue 3 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 191-196
Manuscript Number : CSEIT183350
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

N. Rajganesh, S. Seetha Devi, J. Keerthana, R. Poovizhi, "A Personalized Job Recommended System Using Hybrid Collaborative Filtering Algorithm", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.191-196, March-April-2018.
Journal URL : http://ijsrcseit.com/CSEIT183350

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