Search Engines, Link Analysis, and User's Web Behavior: A Unifying Web Mining Approach

Front Cover
Springer Science & Business Media, Apr 24, 2008 - Computers - 270 pages
2 Reviews
WEB MINING Link Analysis Search Engines User’s Web Behavior HITS Algorithm Fuzzy Cognitive Map Radial Basis Function PageRank Algorithm Interior Point Method Fuzzy Bags Rgeression Models Rough Sets Information Theory Thisbookpresentsaspeci?cand uni?ed approach framework to three- jor components: Search Engines Performance, Link Analysis, and User’s Web Behavior. TheexplosivegrowthandthewidespreadaccessibilityoftheWWW has led to a surge of research activity in the area of information retrieval on VI Preface the WWW. The three aspects of web mining follow the taxonomy of the above diagram: Link Analysis, Search engines, and User’s web behavior are considered in the unifying approach. The book is organized in three sections as follows: 1. In section I of the book (chapters 2–4) we study Link Analysis within the hubs and authorities framework. Link Analysis is the science of hyperlink structures ranking, which are used to determine the relative authority of a Web page and produce improved algorithms for the ranking of Web search results. We use the HITS Algorithm developed by Kleinberg and we propose to study HITS in a 2-D new space: In-degree and Out Degree variables. After we categorize each web page into a speci?c toplogy we study the impact of each web topology on HITS in the new 2-D space. We describe why HITS does not fare well in almost all the di?erent topologies of web graphs. We also describe the PageRank Algorithm in this new 2-D space.
 

What people are saying - Write a review

We haven't found any reviews in the usual places.

Contents

Basic WWW Technologies
1
111 The Internet is Big
2
112 Playing Smart in a Global Trade
3
113 EDI for the Rest of Us
4
115 Technical Challenges Abound
5
12 Web Documents
7
122 Hyperlinks
8
131 Listed Features
12
524 New RBF Interior Point Method Learning Rule
91
525 RBF Training Algorithm for Web Search Engines
93
526 Regression Models Approach for the WWW 87
94
53 Comparing the Results of Regression Models and RBF
96
54 Summary
102
Modeling Human Behavior on the Web
105
62 An Experimentation of Users Web Behavior
107
622 Results on the Fact Based Query
110

132 Search Engine Statistics 1
15
14 Users
19
Web Graphs
23
22 Basic Graph Theory Applied to Web Pages
24
221 Adjacency Matrix Representation of a Web Graph
25
222 Incidence Matrix Representation of a Web Graph
29
223 Bipartite Graphs
30
224 Web Topology
31
225 Web Graphs Topological Difference
34
23 Bow Tie Graphs
35
232 Parametric Characteristics of Bow Tie Graphs
36
233 InOut Degrees Characteristics of Bow Tie Graphs
40
24 Final Observations on Web Graphs
45
Link Analysis of Web Graphs
46
32 Linear Algebra Applied to Link Analysis
48
33 Kleinbergs Algorithm of Link Analysis
49
34 Applying HITS to the Graphs of 22
51
342 HITS applied to Indegree Graphs
53
343 HITS applied to Outdegree Graphs
55
344 HITS Applied to Complete Bipartite Graphs
58
345 HITS Applied to Bipartite Graphs
59
346 Summary of the Application of the HITS Algorithm to the Graphs of 22
61
36 Similarity of Bow Tie Graphs
63
37 Limitations of Link Analysis
67
PageRank Algorithm Applied to Web Graphs
69
42 Page Rank Algorithm Applied to the Graphs of 22
71
421 PageRank Applied to Complete Bipartite Graphs
72
422 PageRank Applied to Outdegree Graphs
74
423 PageRank Applied to Indegree Graphs
75
424 PageRank Applied to Bipartite Graphs
76
426 Summary of the Application of the PageRank Algorithm to the Graphs of 22
77
44 Limitations of PageRank Algorithm
81
Stochastic Simulations Of Search Engines
83
511 Artificial Neural Networks ANN on the WWW
84
512 Rejected World Wide Web Pages
85
52 ANN Metamodel Approach for the WWW
86
521 Training RBF without Correction of Centers Spreads and Weights RBF without CCSW
87
522 Training RBF with Correction of Centers Spreads and Weights using Gradient Descent RBF with CCSW using GD
88
523 Training RBF with Correction of Centers Spreads and Weights using Interior Point Methods RBF with CCSW using IPM
90
A New Model
118
631 Review of Literature on FCM
119
632 Applying FCM to Users Web Behavior
120
633 The Case of Positive Influence of C7 on the Other Concepts
121
634 Final Observation on FCM as a Model for Users Web Behavior
132
64 Multidimensional Fuzzy Bags Modeling Users Web Behavior
136
641 Introduction
137
642 Crisp Bag Modeling Users Actions86
139
643 One Dimensional Fuzzy Bag Modeling Users Actions
144
644 Multidimensional Fuzzy Bags modeling of Users Actions 93
151
645 Discussion and Concluding Remarks
159
65 A Rough Set Theory to Interpret Users Web Behavior
162
652 Rough Set Modeling of User Web Behavior
163
66 Information Theory to Interpret Users Web Behavior
203
Searches Hyperlinks and Web Pages98
204
Searches Time and Web Pages
206
Web Pages Hyperlink Searches and Time
208
664 Final Observation on Rough Set Theory and Information Theory Final to Interpret Users Web Behavior
211
665 General Summary of Rough Set Theory
212
References
216
Graph Theory
225
Interior Point Methods
227
B2 Applying IPM to the Backpropagation Learning Rule
229
B3 Numerical Simulation
232
Regression Models
235
C2 Polynomial Regression
240
C3 Multiple Regression
244
C4 Factorial Regression Analysis of Time
245
C5 Quadratic Response Surface Regression
247
C6 Final Observations on Regression Models
251
Fuzzy Set Theory and Fuzzy Similarity Measures
252
D2 Extending Blondels Measure
255
D3 The New Fuzzy Centrality Score
257
Information Theory
261
E1 Application of Information Theory to a Production Line Problem
262
E2 Application of Rough Set Theory to a Production Line Problem
266
Index
267
Copyright

Other editions - View all

Common terms and phrases

Bibliographic information