Sequence Data Mining

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 existing results on sequence data mining, as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This professional volume fills in the gap, allowing readers to access state-of-the-art results in one place.

Sequence Data Mining is designed for professionals working in bioinformatics, genomics, web services, and financial data analysis. This book is also suitable for advanced-level students in computer science and bioengineering.
Forward by Professor Jiawei Han, University of Illinois at Urbana-Champaign.
 

Table des matières

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.

Résumé

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.

Texte suppl.

From the reviews:

"In this short book, Dong and Pei provide a good introductory to the topic, organized into seven chapters. … This book should appeals to researchers and graduate students working in the field (or with an interest in DM) who want to extend their knowledge of sequence DM." (John Fulcher, Computing Reviews, January, 2008)

Commentaire

From the reviews:

"In this short book, Dong and Pei provide a good introductory to the topic, organized into seven chapters. ... This book should appeals to researchers and graduate students working in the field (or with an interest in DM) who want to extend their knowledge of sequence DM." (John Fulcher, Computing Reviews, January, 2008)

Détails du produit

• Auteurs: Guozh Dong, Guozhu Dong, Jian Pei
• Edition: Springer, Berlin
• Langues: Anglais
• Format d'édition: Livre de poche
• Sortie: 21.10.2010
• EAN: 9781441943521
• ISBN: 978-1-4419-4352-1
• Pages: 150
• Dimensions: 157 mm x 9 mm x 233 mm
• Poids: 264 g
• Illustrations: XVI, 150 p.
• Thèmes: Advances in Database Systems; Advances in Database Systems
• Catégories: Sciences naturelles, médecine, informatique, technique > Informatique, ordinateurs > Informatique; C, Data Mining, Data Warehousing, computer science, Information Retrieval, bioinformatics, Database Management, Computer Vision, pattern recognition, database programming, Life sciences: general issues, Computer Communication Networks, Data Mining and Knowledge Discovery, Information technology: general issues, Computational and Systems Biology, Computational Biology/Bioinformatics, Expert systems / knowledge-based systems, Biometrics, Biometrics (Biology), Information Storage and Retrieval, Computer communication systems, Network hardware