Bing Liu: Web Data Mining | Taschenbuch

Cover: 9783642268915 | Web Data Mining | Exploring Hyperlinks, Contents, and Usage Data | Liu

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Sprache: Englisch

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Beschreibung

Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together 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 and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.

Über den Autor

Bing Liu is a professor of Computer Science at the University of Illinois at Chicago (UIC). He received his PhD in Artificial Intelligence from the University of Edinburgh. Before joining UIC, he was with the National University of Singapore. His current research interests include opinion mining and sentiment analysis, text and Web mining, data mining, and machine learning. He has published extensively in top journals and conferences in these fields. Several of his publications are considered seminal papers of the fields and are highly cited. He has also given more than 30 keynote and invited talks in academia and in industry. On professional services, Liu has served as associate editors of IEEE Transactions on Knowledge and Data Engineering (TKDE), Journal of Data Mining and Knowledge Discovery (DMKD), and SIGKDD Explorations, and is on the editorial boards of several other journals. He has also served as program chairs of IEEE International Conference on Data Mining (ICDM-2010), ACM Conference on Web Search and Data Mining (WSDM-2010), ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2008), SIAM Conference on Data Mining (SDM-2007), ACM Conference on Information and Knowledge Management (CIKM-2006), and Pacific Asia Conference on Data Mining (PAKDD-2002). Additionally, Liu has served extensively as area chairs and program committee members of leading conferences on data mining, Web mining, natural language processing, and machine learning. More information about him can be found from [...]

Zusammenfassung

Covers all key tasks and techniques of Web search and Web mining, i.e., structure mining, content mining, and usage mining

Includes major algorithms from data mining, machine learning, information retrieval and text processing, which are crucial for many Web mining tasks

Contains a rich blend of theory and practice, addressing seminal research ideas and also looking at the technology from a practical point of view

Second edition includes new/revised sections on supervised learning, opinion mining and sentiment analysis, recommender systems and collaborative filtering, and query log mining

Ideally suited for classes on data mining, Web mining, Web search, and knowledge discovery in data bases

Provides internet support with lecture slides and project problems

Includes supplementary material: [...]

Inhaltsverzeichnis

1. Introduction.- Part I: Data Mining Foundations.- 2. Association Rules and Sequential Patterns.- 3. Supervised Learning.- 4. Unsupervised Learning.- 5. Partially Supervised Learning.- Part II: Web Mining.- 6. Information Retrieval and Web Search.- 7. Social Network Analysis.- 8. Web Crawling.- 9. Structured Data Extraction: Wrapper Generation.- 10. Information Integration.- 11. Opinion Mining and Sentiment Analysis.- 12. Web Usage Mining.

Details

Erscheinungsjahr:	2013
Genre:	Informatik , Mathematik , Medizin , Naturwissenschaften , Technik
Rubrik:	Naturwissenschaften & Technik
Medium:	Taschenbuch
Reihe:	Data-Centric Systems and Applications
Inhalt:	xx 624 S. 189 s/w Illustr.
ISBN-13:	9783642268915
ISBN-10:	3642268919
Sprache:	Englisch
Einband:	Kartoniert / Broschiert
Autor:	Liu, Bing
Auflage:	Second Edition 2011
Hersteller:	Springer Springer-Verlag GmbH Data-Centric Systems and Applications
Verantwortliche Person für die EU:	Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße:	235 x 155 x 35 mm
Von/Mit:	Bing Liu
Erscheinungsdatum:	03.08.2013
Gewicht:	0,961 kg