CAREER RECOMMENDER: A NOVEL APPROACH TO SUGGEST JOBS AND POST-GRADUATION STREAMS

Authors

  • Prafful Nath Mathur School of Computing Science and Engineering, VIT University, Chennai, Tamil Nadu, India
  • Abhishek Dixit School of Computing Science and Engineering, VIT University, Chennai, Tamil Nadu, India
  • Sakkaravarthi Ramanathan School of Computing Science and Engineering, VIT University, Chennai, Tamil Nadu, India

DOI:

https://doi.org/10.22159/ajpcr.2017.v10s1.19758

Keywords:

Text Mining, Information Retrieval, Natural Language Processing, Nil, Web crawler

Abstract

To implement a novel approach to recommend jobs and colleges based on résumé of freshly graduated students. Job postings are crawled from web using a web crawler and stored in a customized database. College lists are also retrieved for post-graduation streams and stored in a database. Student résumé is stored and parsed using natural language processing methods to form a résumé model. Text mining algorithms are applied on this model to extract useful information (i.e., degree, technical skills, extracurricular skills, current location, and hobbies). This information is used to suggest matching jobs and colleges to the candidate.

 

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Published

01-04-2017

How to Cite

Mathur, P. N., A. Dixit, and S. Ramanathan. “CAREER RECOMMENDER: A NOVEL APPROACH TO SUGGEST JOBS AND POST-GRADUATION STREAMS”. Asian Journal of Pharmaceutical and Clinical Research, vol. 10, no. 13, Apr. 2017, pp. 365-8, doi:10.22159/ajpcr.2017.v10s1.19758.

Issue

Special Issue April 2017

Section

Original Article(s)

The publication is licensed under CC By and is open access. Copyright is with author and allowed to retain publishing rights without restrictions.

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