Semantic Matching of Web Services Capabilities
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Closing the gap: learning-based information extraction rivaling knowledge-engineering methods
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Resume information extraction with cascaded hybrid model
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
EKAW'06 Proceedings of the 15th international conference on Managing Knowledge in a World of Networks
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A Curriculum Vitae (CV) or a résumé, in general, consists of personal information, education information, work experience, qualifications and preferences parts. Scanning or making structural transformation of the millions of free-formatted résumés from the databases of companies / institutions with human factor will result in the loss of too much time and human effort. In the literature, a limited number of studies have been done to change the résumés of the free-format to a structural format. The overall objective of the study is to infer required information such as user's experience, features, business and education from résumés of the potential user of a human resources system. In this article, we proposed an ontology driven information parsing system that is planned to operate on few millions of résumés to convert them structured format for the purpose of expert finding through the Semantic Web approach.