Successes and New Directions in Data Mining, 1st Edition

  • Published By:
  • ISBN-10: 1599046474
  • ISBN-13: 9781599046471
  • Grade Level Range: College Freshman - College Senior
  • 369 Pages | eBook
  • Original Copyright 2007 | Published/Released December 2007
  • This publication's content originally published in print form: 2007

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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.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Table of Contents.
Detailed Table of Contents.
1: Why Fuzzy Set Theory Is Useful in Data Mining.
2: SeqPAM: A Sequence Clustering Algorithm for Web Personalization.
3: Using Mined Patterns for XML Query Answering.
4: On the Usage of Structural Information in Constrained Semi-Supervised Clustering of XML Documents.
5: Modeling and Managing Heterogeneous Patterns: The PSYCHO Experience.
6: Deterministic Motif Mining in Protein Databases.
7: Data Mining and Knowledge Discovery in Metabolomics.
8: Handling Local Patterns in Collaborative Structuring.
9: Pattern Mining and Clustering on Image Databases.
10: Semantic Integration and Knowledge Discovery for Environmental Research.
11: Visualizing Multi Dimensional Data.
12: Privacy Preserving Data Mining, Concepts, Techniques, and Evaluation Methodologies.
13: Mining Data–Streams.
Compilation of References.
About the Contributors.