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By: Florent Masseglia

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Hardcover | 31 October 2007

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Hardcover
386 Pages

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28.58 x 21.59 x 2.54

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The problem of mining patterns is becoming a very active research area and efficient techniques have been widely applied to problems in industry, government, and science. From the initial definition and motivated by real-applications, the problem of mining patterns not only addresses the finding of itemsets but also more and more complex patterns. Successes and New Directions in Data Mining addresses existing solutions for data mining, with particular emphasis on potential real-world applications. Capturing defining research on topics such as fuzzy set theory, clustering algorithms, semi-supervised clustering, modeling and managing data mining patterns, and sequence motif mining, this book is an indispensable resource for library collections.

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You Can Find This Book In

Non-Fiction Computing & I.T.Databases Data Mining Data Capture & Analysis Economics, Finance, Business and Management

Why Fuzzy Set Theory is Useful in Data Mining	p. 1
SeqPAM: A Sequence Clustering Algorithm for Web Personalization	p. 17
Using Mined Patterns for XML Query Answering	p. 39
On the Usage of Structural Information in Constrained Semi-Supervised Clustering of XML Documents	p. 61
Modeling and Managing Heterogeneous Patterns: The PSYCHO Experience	p. 87
Deterministic Motif Mining in Protein Databases	p. 116
Data Mining and Knowledge Discovery in Metabolomics	p. 141
Handling Local Patterns in Collaborative Structuring	p. 167
Pattern Mining and Clustering on Image Databases	p. 187
Semantic Integration and Knowledge Discovery for Environmental Research	p. 213
Visualizing Multi Dimensional Data	p. 236
Privacy Preserving Data Mining, Concepts, Techniques, and Evaluation Methodologies	p. 277
Mining Data-Streams	p. 302
Table of Contents provided by Blackwell. All Rights Reserved.

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