Successes and new directions in data mining - Masseglia, Florent; Poncelet, Pascal; Teisseire, Maguelonne; Gale Group (Hershey, Penn. Information Science Reference, 2008)
"Addresses existing solutions for data mining, with particular emphasis on potential real-world applications. It captures defining research on topics such as fuzzy set theory, clustering algorithms, semi-supervised clustering, modeling and managing data mining patterns, and sequence motif mining"--Provided by publisher.
Why fuzzy set theory is useful in data mining -- SeqPAM : a sequence clustering algorithm for Web personalization -- Using mined patterns for XML query answering -- On the usage of structural information in constrained semi-supervised clustering of XML documents -- Modeling and managing heterogeneous patterns: the PSYCHO experience -- Deterministic motif mining in protein databases -- Data mining and knowledge discovery in metabolomics -- Handling local patterns in collaborative structuring -- Pattern mining and clustering on image databases -- Semantic integration and knowledge discovery for environmental research -- Visualizing multi dimensional data -- Privacy preserving data mining, concepts, techniques, and evaluation methodologies -- Mining data?streams.
Electronic reproduction.
Keywords: Data mining; Electronic books