Significant Term List Based Metadata Conceptual Mining Model for Effective Text Clustering
- 1 Dr. MGR University, India
- 2 Vel Tech Dr. RR and Dr. SR Technical University, India
Abstract
As the engineering world are growing fast, the usage of data for the day to day activity of the engineering industry also growing rapidly. In order to handle and to find the hidden knowledge from huge data storage, data mining is very helpful right now. Text mining, network mining, multimedia mining, trend analysis are few applications of data mining. In text mining, there are variety of methods are proposed by many researchers, even though high precision, better recall are still is a critical issues. In this study, text mining is focused and conceptual mining model is applied for improved clustering in the text mining. The proposed work is termed as Meta data Conceptual Mining Model (MCMM), is validated with few world leading technical digital library data sets such as IEEE, ACM and Scopus. The performance derived as precision, recall are described in terms of Entropy, F-Measure which are calculated and compared with existing term based model and concept based mining model.
DOI: https://doi.org/10.3844/jcssp.2012.1660.1666
Copyright: © 2012 J. Janet, S. Koteeswaran and E. Kannan. This is an open access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Meta data conceptual mining model
- clustering
- text mining
- data mining