Call For Paper Volume:4 Issue:10 Oct'2017 |

Meta Information Based Text Clustering and Classification with the Use of COATES and COLT Algorithms

Publication Date : 10/07/2015

Author(s) :

Mrunal V. Upasani , Rucha C. Samant.

Conference Name :
4th International Conference on Recent Trends in Engineering & Technology(ICRTET-2015) July 2-4,2015 Organized by SNJB's KBJ College of Engineering,Chandwad,Nashik,Maharashtra,India

Abstract :

Large amount of meta-information is available along with the text documents in many text mining applications. Such meta-information may be of different kinds, such as links in the document, user-access behaviour from web logs which can be useful for data mining. Tremendous amount of information can be found in unstructured attributes for clustering purposes. Therefore, the paper will use an approach which carefully ascertains the coherence of the clustering characteristics of the meta information with that of the text content. For improving the quality of the clustering both the text data and meta information will be helpful. In this paper, the design of an algorithm which combines classical partitioning algorithms with probabilistic models in order to create an effective clustering approach using meta information present in document will be perform. Then it shows how to extend the clustering approach to the classification problem. COATES and COLT algorithm for clustering and classification of text data along with the meta information are presented in this paper and it shows the advantages of using such an approach.

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