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Author Chakrabarti, Soumen.

Title Mining the Web : discovering knowledge from hypertext data / Soumen Chakrabarti.

Imprint San Francisco, CA : Morgan Kaufmann Publishers, ©2003.

Copies

Location Call No. OPAC Message Status
 Axe Elsevier ScienceDirect Ebook  Electronic Book    ---  Available
Description 1 online resource (xviii, 345 pages) : illustrations
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Bibliography Includes bibliographical references (pages 307-327) and index.
Contents Crawling the Web -- Web search and information retrieval -- Similarity and clustering -- Supervised learning -- Semisupervised learning -- Social network analysis -- Resource discovery -- The future of Web mining.
Note Print version record.
Summary 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 issuesincluding Web crawling and indexingChakrabarti 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 workpainstaking, critical, and forward-lookingreaders will gain the theoretical and practical understanding they need to contribute to the Web mining effort. * A comprehensive, critical exploration of statistics-based attempts to make sense of Web Mining. * Details the special challenges associated with analyzing unstructured and semi-structured data. * Looks at how classical Information Retrieval techniques have been modified for use with Web data. * Focuses on today's dominant learning methods: clustering and classification, hyperlink analysis, and supervised and semi-supervised learning. * Analyzes current applications for resource discovery and social network analysis. * An excellent way to introduce students to especially vital applications of data mining and machine learning technology.</li></ul>.
Subject Data mining.
Hypertext systems.
Web databases.
Data Mining
Information Storage and Retrieval -- methods
Internet -- statistics & numerical data
Exploration de données (Informatique)
Hypertexte.
Bases de données sur le Web.
Data mining
Hypertext systems
Web databases
Genre/Form Internet Resources.
Other Form: Print version: Chakrabarti, Soumen. Mining the Web. San Francisco, CA : Morgan Kaufmann Publishers, ©2003 1558607544 9781558607545 (DLC) 2002107241 (OCoLC)50301829
ISBN 9781558607545
1558607544
Standard No. AU@ 000051860598
AU@ 000065313307
CHNEW 001006927
DEBBG BV039832261
DEBBG BV042307620
DEBSZ 405312385
DEBSZ 434184543

 
    
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