Mining the Web

Discovering Knowledge from Hypertext Data
Erscheinungsjahr 2002
ISBN: 978-1-55860-754-5
Verlag: Elsevier Science & Technology

Buch, Englisch, 368 Seiten, Format (B × H): 187 mm x 235 mm, Gewicht: 790 g

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.

Zielgruppe

Researchers and computer science students who are as well as database designers and programmers interested in statistical analysis, machine learning, and data mining techniques applied to large hypertext collections such as the Web.

Autoren/Hrsg.

Chakrabarti, Soumen

Fachgebiete

• Mathematik | Informatik EDV | Informatik Digital Lifestyle Internet, E-Mail, Social Media
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Geowissenschaften Umweltwissenschaften Umwelttechnik
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik

Inhaltsverzeichnis

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.

Über Autor(innen)

Chakrabarti, Soumen
Soumen Chakrabarti is assistant Professor in Computer Science and Engineering at the Indian Institute of Technology, Bombay. Prior to joining IIT, he worked on hypertext databases and data mining at IBM Almaden Research Center. He has developed three systems and holds five patents in this area. Chakrabarti has served as a vice-chair and program committee member for many conferences, including WWW, SIGIR, ICDE, and KDD, and as a guest editor of the IEEE TKDE special issue on mining and searching the Web. His work on focused crawling received the Best Paper award at the 8th International World Wide Web Conference (1999). He holds a Ph.D. from the University of California, Berkeley.