Liu Web Data Mining

Exploring Hyperlinks, Contents, and Usage Data
2007
ISBN: 978-3-540-37882-2
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 552 Seiten, eBook

Reihe: Data-Centric Systems and Applications

This book provides a comprehensive text on Web data mining. Key topics of structure mining, content mining, and usage mining are covered. The book brings together all the essential concepts and algorithms from related areas such as data mining, machine learning, and text processing to form an authoritative and coherent text. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining. Lecturers can readily use it for classes on data mining, Web mining, and Web search. Internet support with lecture slides and project problems is available online.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Liu, Bing

Inhaltsverzeichnis

Data Mining Foundations.- Association Rules and Sequential Patterns.- Supervised Learning.- Unsupervised Learning.- Partially Supervised Learning.- Web Mining.- Information Retrieval and Web Search.- Link Analysis.- Web Crawling.- Structured Data Extraction: Wrapper Generation.- Information Integration.- Opinion Mining.- Web Usage Mining.

Über Autor(innen)

Bing Liu is an associate professor in Computer Science at the University of Illinois at Chicago (UIC). He received his PhD degree in Artificial Intelligence from the University of Edinburgh. Before joining UIC in 2002, he was with the National University of Singapore. His research interests include data mining, Web mining, text mining, and machine learning. He has published extensively in these areas in leading conferences and journals. He served (or serves) as a vice chair, deputy vice chair or program committee member of many conferences, including WWW, KDD, ICML, VLDB, ICDE, AAAI, SDM, CIKM and ICDM.