Data Mining Patterns: New Methods and Applications

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.

The many academic areas covered in this publication include, but are not limited to:

• Bi-directional constraint pushing
• Class-labeled data
• Data Visualization
• Frequent pattern mining
• Hierarchical Bayesian mixed-membership models
• Latent patterns
• Metric methods in data mining
• Mining hyperclique patterns
• Mining XML documents
• Noisy document streams
• Pattern discovery in biosequences
• Social Network Mining
• Spatio-textual association rules
• Summarizing data cubes
• Topic and cluster evolution