Mining Sequential Patterns from Large Data Sets by Wei Wang
In many applications, e.g., bioinformatics, web access traces, system u- lization logs, etc., the data is naturally in the form of sequences. It has been of great interests to analyze the sequential data to find their inherent char- teristics. The sequential pattern is one of the most widely studied models to capture such characteristics. Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. In this book, we focus on sequential pattern mining. To meet different needs of various applications, several models of sequential patterns have been proposed. We do not only study the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. The objective of this book is to provide computer scientists and domain - perts such as life scientists with a set of tools in analyzing and understanding the nature of various sequences by : (1) identifying the specific model(s) of - quential patterns that are most suitable, and (2) providing an efficient algorithm for mining these patterns. Chapter 1 INTRODUCTION Data Mining is the process of extracting implicit knowledge and discovery of interesting characteristics and patterns that are not explicitly represented in the databases. The techniques can play an important role in understanding data and in capturing intrinsic relationships among data instances. Data mining has been an active research area in the past decade and has been proved to be very useful.-
Fuzzy Database Modeling with XML
-
Advances in Digital Government
-
Quantifiers in Action
-
Advanced Database Indexing
-
Database Issues in Geographic Information Systems
-
Advanced Signature Indexing for Multimedia and Web Applications
-
Searching Multimedia Databases by Content
-
Time-Constrained Transaction Management
-
Fuzzy Logic in Data Modeling
-
Access to Mobile Services
-
Index Data Structures in Object-Oriented Databases
-
Database Recovery
-
Managing and Mining Graph Data
-
Association Rule Hiding for Data Mining
-
Parallel, Object-Oriented, and Active Knowledge Base Systems
-
Information Brokering Across Heterogeneous Digital Data
-
Mutation Testing for the New Century
-
Database Concurrency Control
-
The Fractal Structure of Data Reference
-
Object Relationship Notation (ORN) for Database Applications
-
Stream Data Processing: A Quality of Service Perspective
-
Managing and Mining Uncertain Data
-
Stream Data Management
-
Interconnecting Heterogeneous Information Systems
-
Mining Very Large Databases with Parallel Processing
-
Foundations of Knowledge Systems
-
Data Management for Mobile Computing
-
Similarity Search
-
Middleware Networks
-
Information and Database Quality
-
Indexing Techniques for Advanced Database Systems
-
Replication Techniques in Distributed Systems
-
Multilevel Secure Transaction Processing
| SKU | Unavailable |
| ISBN 13 | 9781441937070 |
| ISBN 10 | 1441937072 |
| Title | Mining Sequential Patterns from Large Data Sets |
| Author | Wei Wang |
| Series | Advances In Database Systems |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer-Verlag New York Inc. |
| Year published | 2010-12-06 |
| Number of pages | 163 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |