A Review on Classification of Text Data using Meta Data

Author(s):

Mr. Vishal Annasaheb Musmade , SVIT nashik; Prof. S. M. Rokade

Keywords:

Text data mining, categorization, side information, clustering, metadata

Abstract:

In today’s digital environment, text databases are rapidly increases due to use of internet and communication mediums. Different text mining techniques are used for knowledge discovery and Information retrieval. Text data contains the side information along with the text data. Metadata may be the side information associated with text data like author, co-author or citation network, document provenance information, web links or other kind of data which provide more insights about the text documents. Such metadata contains tremendous amount of information for the clustering purpose. Using such metadata in the categorization process provides more refine clustered data. But sometimes side information may be noisy and results in wrong categorization which decreases the quality of clustering process. Therefore, a new approach for mining of text data using metadata is suggested, which combines partitioning approach with probabilistic estimation model for the mining of text data along with the metadata.

Other Details:

Manuscript Id	:	IJSTEV3I5075
Published in	:	Volume : 3, Issue : 5
Publication Date	:	01/12/2016
Page(s)	:	98-100

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