This book constitutes the thoroughly refereed post-proceedings of the 7th International Workshop on Mining Web Data, WEBKDD 2005, held in Chicago, IL, USA in August 2005 in conjunction with the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2005. The nine revised full papers presented together with a detailed preface went through two rounds of reviewing and improvement and were carefully selected for inclusion in the book.
Author(s): Olfa Nasraoui, Osmar Zaiane, Myra Spiliopoulou, Manshad Mobasher
Series: Lecture Notes in Artificial Intelligence 4198
Edition: 1
Publisher: Springer
Year: 2006
Language: English
Pages: 185
Front matter......Page 1
Introduction......Page 9
URL Abstraction......Page 10
Clustering User Sessions of Clickstream Data......Page 11
Generating Usage Patterns......Page 12
Methodology......Page 13
Create Sub-abstracted Sessions......Page 14
Session Sequence Alignment......Page 15
Generating Significant Usage Patterns......Page 17
Clickstream Data......Page 19
Result Analysis......Page 20
Conclusion and Future Work......Page 23
References......Page 24
Introduction......Page 26
Related Work......Page 28
The AP-IP Frequent Subgraph Mining Problem......Page 29
The fAP-IP Algorithm......Page 30
Graph Clustering for Finding Individual Patterns......Page 33
Time and Space Requirements......Page 34
Pre-processing: Graph Partitioning for Finding Conceptual Transaction Structure......Page 38
AP-IP Visualization......Page 39
Data......Page 40
Results......Page 41
Conclusions and Outlook......Page 44
Introduction......Page 47
Collaborative Filtering......Page 49
Ontology Reasoning......Page 50
Basic Idea......Page 52
Definitions......Page 55
HAPPL Process......Page 57
Experimental Results......Page 59
Overall Performance Analysis......Page 60
Discussion......Page 62
References......Page 64
Introduction......Page 66
About Collaborative Filtering......Page 67
Memory-Based Approach to Collaborative Filtering......Page 68
Model-Based Approaches to Collaborative Filtering......Page 69
Some Other Approaches......Page 71
Collaborative Filtering Data Characteristics......Page 72
Evaluation Platform......Page 73
Data Description......Page 74
Experimental Setting......Page 77
Evaluation Results......Page 79
Conclusions and Future Work......Page 81
Introduction......Page 85
Related Work......Page 86
The Problem......Page 87
Philosophical......Page 88
Technical......Page 89
System Architecture......Page 93
Individual Test Cases and Descriptions......Page 95
Results......Page 97
Summary......Page 100
Conclusions......Page 101
References......Page 102
Introduction......Page 104
Framework for Characterizing Profile Injection Attacks......Page 106
Basic Attack Models......Page 107
The Segment Attack Model......Page 110
User-Based Collaborative Filtering......Page 112
Item-Based Collaborative Filtering......Page 113
Evaluation Metrics......Page 114
Attacks Against User-Based Collaborative Filtering......Page 115
Attacks Against Item-Based Collaborative Filtering......Page 116
Attack Profile Classification......Page 118
Generic Attributes for Detection......Page 119
Model-Specific Attributes for Detection......Page 120
Detection Experimental Results......Page 121
Conclusions......Page 124
Introduction......Page 127
Related Work......Page 129
An Overview of Cluster Maintenance......Page 130
Relational Fuzzy Subtractive Clustering (RFSC)......Page 132
Maintenance Scheme for RFSC......Page 133
Impact Factor......Page 135
Similarity Analysis......Page 137
Detection of New Interest Areas......Page 139
Adaptive Usage Profiling for Web Personalization......Page 142
Conclusions and Future Work......Page 143
References......Page 144
Introduction......Page 147
Micro-clustering and Quantitative Change Detection......Page 148
Change Detection for Text and Categorical Data......Page 152
Online Community Evolution in Data Streams......Page 154
Online Summarization of Graphical Data Streams......Page 155
Offline Construction and Processing of Differential Graphs......Page 158
Finding Evolving Communities......Page 159
Subroutines for Determination of the Communities......Page 160
Conclusions and Summary......Page 163
Introduction......Page 166
Related Work......Page 168
Personalized Results......Page 169
Learning UIH......Page 171
Four Characteristics of a Term......Page 173
Scoring a Term......Page 175
Incorporating Public Page Score......Page 176
Experiments......Page 177
Interesting Web Page......Page 178
Potentially Interesting Web Page......Page 180
Conclusion......Page 181
References......Page 182
Back matter......Page 185
