Sequential data from Web server logs, online transaction logs, and performance measurements is collected each day. This sequential data is a valuable source of information, as it allows individuals to search for a particular value or event and also facilitates analysis of the frequency of certain events or sets of related events. Finding patterns in sequences is of utmost importance in many areas of science, engineering, and business scenarios.Pattern Discovery Using Sequence Data Mining: Applications and Studies provides a comprehensive view of sequence mining techniques and presents current research and case studies in pattern discovery in sequential data by researchers and practitioners. This research identifies industry applications introduced by various sequence mining approaches.
Author(s): Pradeep Kumar
Edition: 1
Publisher: IGI Global
Year: 2011
Language: English
Pages: 286
Tags: Информатика и вычислительная техника;Искусственный интеллект;Интеллектуальный анализ данных;
Title......Page 2
Copyright Page......Page 3
Editorial Advisory Board......Page 4
Table of Contents......Page 5
Preface......Page 8
Section 1......Page 12
Applications of Pattern Discovery Using Sequential Data Mining......Page 14
A Review of Kernel Methods Based Approaches to Classification and Clustering of Sequential Patterns, Part I......Page 37
A Review of Kernel Methods Based Approaches to Classification and Clustering of Sequential Patterns, Part II......Page 64
Section 2......Page 85
Mining Statistically Significant Substrings Based on the Chi-Square Measure......Page 86
Unbalanced Sequential Data Classification using Extreme Outlier Elimination and Sampling Techniques......Page 96
Quantization based Sequence Generation and Subsequence Pruning for Data Mining Applications......Page 107
Classification of Biological Sequences......Page 124
Section 3......Page 149
Approaches for Pattern Discovery Using Sequential Data Mining......Page 150
Analysis of Kinase Inhibitors and Druggability of Kinase-Targets Using Machine Learning Techniques......Page 168
Identification of Genomic Islands by Pattern Discovery......Page 179
Video Stream Mining for On-Road Traffic Density Analytics......Page 195
Discovering Patterns in Order to Detect Weak Signals and Define New Strategies......Page 208
Discovering Patterns for Architecture Simulation by Using Sequence Mining......Page 225
Sequence Pattern Mining for Web Logs......Page 250
Compilation of References......Page 257
About the Contributors......Page 277
Index......Page 283
