Resume Refinement System using Semantic Analysis


Authors : Ruchita Haresh Makwana, Aishwarya Mohan Medhekar, Bhavika Vishanji Mrug.

Volume/Issue : Volume 3 - 2018, Issue 3 - March

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/PJezQ3

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

The Resume Refinement System focuses on online recruitment process, where the recruiter uses this system to hire the suitable candidate. Recruiter post the job-post, where the candidates upload their resumes and based on semantic analysis the web application will provide the list of shortlisted candidates to the recruiters. Since web documents have different formats and contents; it is necessary for various documents to use standards to normalize their modeling in order to facilitate retrieval task. The model must take into consideration, both the syntactic structure, and the semantic content of the documents. Resume is the document that summaries our education, skills, accomplishments, and experience. Job seekers submit their Resume via the web. Therefore, in their recruitment process, companies are requiring systems for extraction and analysis of information from Resume: identifying specific patterns, which meet with certain profile. To extract the essential component of Resumes and to relate them with recruiter’s requirements needs first, a study of their most significant elements and a better understanding of the resume feature. This work focuses on resume analysis.

Keywords : Online recruitment, semantic analysis, neural network, missing background knowledge.

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