Sequence Data Mining (Advances in Database Systems, Band 33) - Softcover

Dong, Guozhu; Pei, Jian

Softcover

ISBN 10: 1441943528 ISBN 13: 9781441943521

Verlag: Springer, 2010

Inhaltsangabe

This book 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 volume fills in the gap, allowing readers to access the 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.

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Über die Autorin bzw. den Autor

Dr. Guozhu Dong is a professor of Computer Science and Engineering, and a member at the Knoesis Center of Excellence, at Wright State University. He received a Ph.D. in Computer Science from the University of Southern California and a B.S. in Mathematics from Shandong Univerity. Before joining Wright State University, he was a faculty member at the University of Melbourne. His research interests span data mining, machine learning, databases, data science, bioinformatics, and artificial intelligence. He co-authored a book on Sequence Data Mining, co-edited two books on Contrast Data Mining and on Feature Engineering, respectively, and authored a book on Exploiting the Power of Group Differences. He is known for his pioneering work and sustained effort on emerging/contrast pattern mining and on the use of such patterns in problem solving. He has published hundreds of papers at major international conferences and in top-rate journals in the fields of data mining and databases. He received several best research paper awards at major data mining conferences. At Wright State University, he was recognized for Excellence in Research in his college. He has served on hundreds of program committees of international conferences, and he has chaired the program committees for several such conferences. He is a senior member of both ACM and IEEE.

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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.

 

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2010
• Sprache: Englisch
• ISBN 10: 1441943528
• ISBN 13: 9781441943521
• Einband: Taschenbuch
• Anzahl der Seiten: 168
• Kontakt zum Hersteller: GPSR Kontakt; ProductSafety@springernature.com; ; Slevogtstraße 3-5; Heidelberg; 69126; Deutschland