Data Mining the Web Uncovering Patterns in Web Content, Structure, and Usage [Hardcover]

This book introduces the reader to methods of data mining on the web, including uncovering patterns in web content (classification, clustering, language processing), structure (graphs, hubs, metrics), and usage (modeling, sequence analysis, performance).PREFACE.

PART I: WEB STRUCTURE MINING.

1 INFORMATION RETRIEVAL AND WEB SEARCH.

Web Challenges.

Web Search Engines.

Topic Directories.

Semantic Web.

Crawling the Web.

Web Basics.

Web Crawlers.

Indexing and Keyword Search.

Document Representation.

Implementation Considerations.

Relevance Ranking.

Advanced Text Search.

Using the HTML Structure in Keyword Search.

Evaluating Search Quality.

Similarity Search.

Cosine Similarity.

Jaccard Similarity.

Document Resemblance.

References.

Exercises.

2 HYPERLINK-BASED RANKING.

Introduction.

Social Networks Analysis.

PageRank.

Authorities and Hubs.

Link-Based Similarity Search.

Enhanced Techniques for Page Ranking.

References.

Exercises.

PART II: WEB CONTENT MINING.

3 CLUSTERING.

Introduction.

Hierarchical Agglomerative Clustering.

k-Means Clustering.

Probabilty-Based Clustering.

Finite Mixture Problem.

Classification Problem.

Clustering Problem.

Collaborative Filtering (Recommender Systemlc%