A fast algorithm for discovering categories and attribute relevance in web data

Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Volumn 2002-January, Issue , 2002, Pages 280-285

  Frigui, H ^a   Nasraoui, F ^a  

^a University of Memphis   (United States)

Author keywords

Clustering algorithms; Data mining; Frequency; Fuzzy sets; Information retrieval; Search engines; Uniform resource locators; Unsupervised learning; Web mining; Web server

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); DATA MINING; FEATURE EXTRACTION; FUZZY SETS; INFORMATION RETRIEVAL; INFORMATION SCIENCE; LEARNING ALGORITHMS; SEARCH ENGINES; UNSUPERVISED LEARNING; WEB SERVICES; WEBSITES; WORLD WIDE WEB;

ATTRIBUTE WEIGHT; CLASSIFIER SYSTEMS; DISCRIMINATIVE FEATURES; FREQUENCY; K-MEANS CLUSTERING ALGORITHM; SCALABLE IMPLEMENTATION; WEB MINING; WEB SERVERS;

CLUSTERING ALGORITHMS;

EID: 84871138428     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NAFIPS.2002.1018070     Document Type: Conference Paper

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