Mining the Web: Discovering Knowledge for Hypertext Data (網路挖掘：發現超文本資料的知識)

Mining the Web: Discovering Knowledge from Hypertext Data is the first book devoted entirely to techniques for producing knowledge from the vast body of unstructured Web data. Building on an initial survey of infrastructural issues--including Web crawling and indexing--Chakrabarti examines low-level machine learning techniques as they relate specifically to the challenges of Web mining. He then devotes the final part of the book to applications that unite infrastructure and analysis to bring machine learning to bear on systematically acquired and stored data. Here the focus is on results: the strengths and weaknesses of these applications, along with their potential as foundations for further progress. From Chakrabarti's work--painstaking, critical, and forward-looking--readers will gain the theoretical and practical understanding they need to contribute to the Web mining effort.

Contents

Preface. Introduction. I Infrastructure: Crawling the Web. Web search. II Learning: Similarity and clustering. Supervised learning for text. Semi-supervised learning. III Applications: Social network analysis. Resource discovery. The future of Web mining.