Abstract
The research area identification is a challenging issue to solve as there lakhs of millions of research papers available, it is required to classify the papers based on primary and secondary areas. The existing text mining techniques classifies research documents in the static manner. So there is a need to develop a framework that can classify the research documents in dynamic manner. This paper mainly describes a framework that can classify area of research documents arrived to the repository. The proposed frame work consists of two phases where first is to construct word list for each area of the paper. In second phase it continuously updates the word list associated to the new stream of research documents. The experimental results compared with existing techniques are reported and that satisfies the minimum requirement.
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Priyanka, J.S.V.S.H., Rani, J.S., Deepthi, K.S., Kranthi, T. (2015). Information Tracking from Research Papers Using Classification Techniques. In: Satapathy, S., Govardhan, A., Raju, K., Mandal, J. (eds) Emerging ICT for Bridging the Future - Proceedings of the 49th Annual Convention of the Computer Society of India (CSI) Volume 1. Advances in Intelligent Systems and Computing, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-319-13728-5_17
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DOI: https://doi.org/10.1007/978-3-319-13728-5_17
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13727-8
Online ISBN: 978-3-319-13728-5
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