Welcome to IOU Digital Library

This comprehensive reference collects authoritative chapters on data-mining theory and practice, covering a broad range of topics — from fundamental algorithms (classification, clustering, association, anomaly detection) to advanced techniques (web mining, text mining, large-scale data processing, privacy issues). Written by leading experts, it serves as a thorough guide for researchers, data scientists, and advanced practitioners seeking both theoretical foundations and practical applications in data mining.

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245: $a: Data Mining: Know It All
245: $b:
082: $a:
100: $a: Soumen Chakrabarti & Earl Cox & Eibe Frank & Ralf Hartmut Güting & Jaiwei Han & Xia Jiang & Micheline Kamber & Sam S. Lightstone
650: $a: Data mining
250: $a:
440: $v:
250: $b: Morgan Kaufmann (an imprint of Elsevier)
250: $c: 2009
020: $a: 978-0-12-374629-0
300: $a: 1632