Sequence Data Mining

• Main Authors: Dong, Guozhu (Author), Pei, Jian (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Boston, MA : Springer US, 2007.
• Series: Advances in Database Systems, 33
• Subjects: Computer science.; Computer communication systems.; Database management.; Data mining.; Information storage and retrieval.; Biometrics (Biology).; Bioinformatics.; Computer Science.; Database Management.; Data Mining and Knowledge Discovery.; Information Storage and Retrieval.; Computational Biology/Bioinformatics.; Biometrics.; Computer Communication Networks.

Understanding sequence data, and the ability to utilize this hidden knowledge, creates a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more. Sequence Data Mining provides balanced coverage of the...

Table of Contents:

• 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.