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Data Mining Patterns: New Methods and Applications

Data Mining Patterns: New Methods and Applications

Copyright: © 2008 |Pages: 324
ISBN13: 9781599041629|ISBN10: 1599041626|EISBN13: 9781599041643|ISBN13 Softcover: 9781616926519
DOI: 10.4018/978-1-59904-162-9
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MLA

Poncelet, Pascal, et al., editors. Data Mining Patterns: New Methods and Applications. IGI Global, 2008. https://doi.org/10.4018/978-1-59904-162-9

APA

Poncelet, P., Masseglia, F., & Teisseire, M. (Eds.). (2008). Data Mining Patterns: New Methods and Applications. IGI Global. https://doi.org/10.4018/978-1-59904-162-9

Chicago

Poncelet, Pascal, Florent Masseglia, and Maguelonne Teisseire, eds. Data Mining Patterns: New Methods and Applications. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-162-9

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Since the introduction of the Apriori algorithm a decade ago, the problem of mining patterns is becoming a very active research area, and efficient techniques have been widely applied to the problems either in industry or science. Currently, the data mining community is focusing on new problems such as: mining new kinds of patterns, mining patterns under constraints, considering new kinds of complex data, and real-world applications of these concepts.

Data Mining Patterns: New Methods and Applications provides an overall view of the recent solutions for mining, and also explores new kinds of patterns. This book offers theoretical frameworks and presents challenges and their possible solutions concerning pattern extractions, emphasizing both research techniques and real-world applications. Data Mining Patterns: New Methods and Applications portrays research applications in data models, techniques and methodologies for mining patterns, multi-relational and multidimensional pattern mining, fuzzy data mining, data streaming, incremental mining, and many other topics.

Table of Contents

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Front Materials
Title Page
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Copyright Page
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Preface
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Acknowledgment
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Chapters
Back Materials
About the Editors
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Compilation of References
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About the Contributors
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Index
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