Publications

Sequence Data Mining
Series: Advances in Database Systems
Guozhu Dong and Jian Pei
Springer, 2007
ISBN-13: 978-0-387-69936-3

Sequence data is pervasive in our lives, and understanding sequence data is of grand importance. Much research has been conducted on sequence data mining in the last dozen years. Hundreds if not thousands of research papers have been published in forums of various disciplines, such as data mining, database systems, information retrieval, biology and bioinformatics, industrial engineering, etc. The area of sequence data mining has developed rapidly, producing a diversified array of concepts, techniques and algorithmic tools. The purpose of this book is to provide, in one place, a concise introduction to the field of sequence data mining, and a fairly comprehensive overview of the essential research results.

This monograph can be useful to academic researchers and graduate students interested in data mining in general and in sequence data mining in particular, and to scientists and engineers working in fields where sequence data mining is involved, such as bioinformatics, genomics, web services, security, and financial data analysis.

Chapter titles:
1. Introduction
2. Frequent and Closed Sequence Patterns
3 Classification, Clustering, Features and Distances of Sequence Data .
4 Sequence Motifs: Identifying and Characterizing Sequence Families
5. Mining Partial Orders from Sequences
6 Distinguishing Sequence Patterns
7 Related Topics

The book provides a list of 134 references on sequence data mining and analysis.