Please use this identifier to cite or link to this item: http://ir.inflibnet.ac.in/handle/1944/374
Title: Data Mining Techniques for Information Retrieval
Authors: Mukhopadhyay, Bikash
Mukhopadhyay, Sripati
Keywords: Data Mining
Text Mining
Web Searching
Natural Language Processing
Machine Learning
Issue Date: Feb-2004
Publisher: INFLIBNET Centre, Ahmedabad
Abstract: Data mining automatically and exhaustively explores very large datasets, consequently uncovering otherwise hidden relationships among data. This technology has been successfully applied in science, health, marketing and finance to aid new discoveries and strengthen markets. In addition, data mining techniques are being applied to discover and organize information from the Web. Unfortunately these advancements in data storage and distribution technology have not been accompanied by respective research in data retrieval technology for a long time. To put it in short: we are now being flooded with data, yet we are starving for knowledge. This need has created an entirely new approach to data processing - the data mining, which concentrates on finding important trends and meta-information in huge amounts of raw data. In this paper the main concepts of data mining and automatic knowledge discovery in databases are presented (clustering, finding association rules, categorisation, statistical analysis).
URI: http://hdl.handle.net/1944/374
ISBN: 81-900825-8-2
Appears in Collections:CALIBER 2004:New Delhi

Files in This Item:
File Description SizeFormat 
04cali_66.pdf65.66 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.