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Intelligent Data Mining Assistance

Michel Charest

ISBN 10: 3639119592 / ISBN 13: 9783639119596
Published by VDM Verlag
New Condition: New Soft cover
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About this Item

112 pages. Dimensions: 8.6in. x 5.7in. x 0.4in.Nowadays, decision makers in competitive and diverse business sectors must make informed decisions about strategic problems. Such problems are often complex enough to warrant the use of sophisticated analytical methods for their resolution (i. e. forecasting, classification, etc. ). Having borrowed from the myriad of techniques and models available from the areas of machine learning and statistics, data mining (DM) has become a very specialized field. Consequently, the effective application of DM is littered with many difficult and technical decisions (i. e. data cleansing, feature transformations, algorithm and parameter selection, model evaluation). Most data mining products provide a large number of models and tools, but few provide intelligent assistance. Moreover, research seems to be based on utterly specialized DM techniques, rather than focusing on strategic, methodological, and even epistemological aspects of DM. As a result, the following work attempts to verify if the use of a case-based reasoning system and other AI techniques will provide an adequate environment for the reuse of data mining knowledge with the intention of better supporting the decision making process. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Bookseller Inventory # 9783639119596

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Bibliographic Details

Title: Intelligent Data Mining Assistance

Publisher: VDM Verlag

Binding: Paperback

Book Condition:New

Book Type: Paperback

About this title

Synopsis:

Nowadays, decision makers in competitive and diverse business sectors must make informed decisions about strategic problems. Such problems are often complex enough to warrant the use of sophisticated analytical methods for their resolution (i.e. forecasting, classification, etc.). Having borrowed from the myriad of techniques and models available from the areas of machine learning and statistics, data mining (DM) has become a very specialized field. Consequently, the effective application of DM is littered with many difficult and technical decisions (i.e. data cleansing, feature transformations, algorithm and parameter selection, model evaluation). Most data mining products provide a large number of models and tools, but few provide "intelligent" assistance. Moreover, research seems to be based on utterly specialized DM techniques, rather than focusing on strategic, methodological, and even epistemological aspects of DM. As a result, the following work attempts to verify if the use of a case-based reasoning system and other AI techniques will provide an adequate environment for the reuse of data mining knowledge with the intention of better supporting the decision making process.

About the Author:

is a Systems Analyst specializing in the development of Business Intelligence, Data Warehousing and Data Mining applications at the University of Quebec at Trois-Rivieres, Canada. Michel Charest holds an M.Sc. degree in Applied Mathematics and Computer Science and a Bachelor's degree in Computer Engineering.

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