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Understanding sequence data, and the ability to utilize this hidden knowledge, will create a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more.

This book provides thorough coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods. It offers balanced coverage on data mining and sequence data analysis, allowing readers to access the state-of-the-art results in one place.

Sequence Data Mining

Frequent and Closed Sequence Patterns.- Classification, Clustering, Features and Distances of Sequence Data.- Sequence Motifs: Identifying and Characterizing Sequence Families.- Mining Partial Orders from Sequences.- Distinguishing Sequence Patterns.- Related Topics.