Automated Profile Extraction and Classification with Stanford Algorithm
Renuka S. Anami1, Gauri R. Rao2

1Renuka S. Anami, M.Tech. Student, Department of Computer Engineering, Bharati Vidyapeeth College of Engineering, Pune (Maharashtra), India.
2Gauri R. Rao, Associate, Professor, Department of Computer Engineering, Bharati Vidyapeeth College of Engineering, Pune (Maharashtra), India.
Manuscript received on 10 December 2014 | Revised Manuscript received on 20 December 2014 | Manuscript Published on 30 December 2014 | PP: 67-71 | Volume-4 Issue-7, December 2014 | Retrieval Number: G1916124714/14©BEIESP
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Abstract: The enterprises and multinational companies receive thousands of resumes from the job seekers during this Internet era. Currently available filtering techniques and search services provide the recruiters to filter thousands of resumes to few hundred potential ones. It is difficult to identify the potential resumes by examining each resume, since these filtered resumes are similar to each other. We are investigating the issues related to the development of approaches to improve the performance of resume selection process. We have extended the concept of special features and also proposed an approach to identify resumes with special skills. In the literature, the concepts of special features have been applied to improve the process of candidate selection in E-commerce environment. As resumes contain unformatted text or semi-formatted text, extending the concept of special features for the development of approach to process resumes is a complex task. Only skills related formation of the resumes is obtained by considering this system approach. The experimental results of the real world set of resumes show that the proposed approach has the potential to improve the process of resume selection. An effective way of an approach for extraction of information from the resumes is achieved by the system .It supports routing and management of resumes automatically. The framework of an IE gives the extraction process of resumes along with the required information regarding the algorithms related with this extraction. The overall objective of the study is to provide the required information about the skills and experience to human resource system. This system provides the resumes to be extracted in a structured format for the semantic web approach.
Keywords: NLP, HTML, JAVA, Candidate Profile, Information Extraction (IE), CSS.

Scope of the Article: Classification