Text mining : a burgeroning quality improvement tool

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2007
J.Mohammad, Mohammad Alkin
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While the amount of textual data available to us is constantly increasing, managing the texts by human effort is clearly inadequate for the volume and complexity of the information involved. Consequently, requirement for automated extraction of useful knowledge from huge amounts of textual data to assist human analysis is apparent. Text mining (TM) is mostly an automated technique that aims to discover knowledge from textual data. In this thesis, the notion of text mining, its techniques, applications are presented. In particular, the study provides the definition and overview of concepts in text categorization. This would include document representation models, weighting schemes, feature selection methods, feature extraction, performance measure and machine learning techniques. The thesis details the functionality of text mining as a quality improvement tool. It carries out an extensive survey of text mining applications within service sector and manufacturing industry. It presents two broad experimental studies tackling the potential use of text mining for the hotel industry (the comment card analysis), and in automobile manufacturer (miles per gallon analysis). Keywords: Text Mining, Text Categorization, Quality Improvement, Service Sector, Manufacturing Industry.
Mathematics, Scientific computig (general)
http://etd.lib.metu.edu.tr/upload/2/12609006/index.pdf
https://hdl.handle.net/11511/17341
Graduate School of Applied Mathematics, Thesis

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Citation Formats
M. A. J.Mohammad, “Text mining : a burgeroning quality improvement tool,” M.S. - Master of Science, Middle East Technical University, 2007.
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