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Part III: Applications
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Part III: Applications
by Soumen Chakrabarti
Mining the Web
Cover
Title Page
Copyright
Foreword
Preface
Table of Contents
Chapter 1: Introduction
1.1 Crawling and Indexing
1.2 Topic Directories
1.3 Clustering and Classification
1.4 Hyperlink Analysis
1.5 Resource Discovery and Vertical Portals
1.6 Structured vs. Unstructured Data Mining
1.7 Bibliographic Notes
Part I: Infrastructure
Chapter 2: Crawling the Web
2.1 HTML and HTTP Basics
2.2 Crawling Basics
2.3 Engineering Large-Scale Crawlers
2.4 Putting Together a Crawler
2.5 Bibliographic Notes
Chapter 3: Web Search and Information Retrieval
3.1 Boolean Queries and the Inverted Index
3.2 Relevance Ranking
3.3 Similarity Search
3.4 Bibliographic Notes
Part II: Learning
Chapter 4: Similarity and Clustering
4.1 Formulations and Approaches
4.2 Bottom-Up and Top-Down Partitioning Paradigms
4.3 Clustering and Visualization via Embeddings
4.4 Probabilistic Approaches to Clustering
4.5 Collaborative Filtering
4.6 Bibliographic Notes
Chapter 5: Supervised Learning
5.1 The Supervised Learning Scenario
5.2 Overview of Classification Strategies
5.3 Evaluating Text Classifiers
5.4 Nearest Neighbor Learners
5.5 Feature Selection
5.6 Bayesian Learners
5.7 Exploiting Hierarchy among Topics
5.8 Maximum Entropy Learners
5.9 Discriminative Classification
5.10 Hypertext Classification
5.11 Bibliographic Notes
Chapter 6: Semisupervised Learning
6.1 Expectation Maximization
6.2 Labeling Hypertext Graphs
6.3 Co-training
6.4 Bibliographic Notes
Part III: Applications
Chapter 7: Social Network Analysis
7.1 Social Sciences and Bibliometry
7.2 PageRank and HITS
7.3 Shortcomings of the Coarse-Grained Graph Model
7.4 Enhanced Models and Techniques
7.5 Evaluation of Topic Distillation
7.6 Measuring and Modeling the Web
7.7 Bibliographic Notes
Chapter 8: Resource Discovery
8.1 Collecting Important Pages Preferentially
8.2 Similarity Search Using Link Topology
8.3 Topical Locality and Focused Crawling
8.4 Discovering Communities
8.5 Bibliographic Notes
Chapter 9: The Future of Web Mining
9.1 Information Extraction
9.2 Natural Language Processing
9.3 Question Answering
9.4 Profiles, Personalization, and Collaboration
References
Index
About the Author
Instructions for online access
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Chapter 6: Semisupervised Learning
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Chapter 7: Social Network Analysis
Part III
Applications
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