The hybrid representation model for web document classification

International Journal of Intelligent Systems

Volumn 23, Issue 6, 2008, Pages 654-679

  Markov, A ^a   Last, M ^a   Kandel, A ^b  

^a BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

^b University of South Florida   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CATEGORIZATION METHODS; CLASSIFICATION ACCURACIES; CLASSIFICATION ALGORITHMS; CLASSIFICATION TIME; DOCUMENT REPRESENTATIONS; GRAPH-BASED; HTML TAGS; HYBRID APPROACHES; HYBRID METHODS; K NEAREST NEIGHBOR (K-NN); MODEL BASED (OPC); MODEL BASED CLASSIFIERS; NAIVE BAYES CLASSIFIER (NBC); REPRESENTATION MODEL; RETRIEVAL (MIR); SIGNIFICANT REDUCTION; STRUCTURAL INFORMATIONS; VECTOR REPRESENTATION (VREP); VECTOR SPACE MODEL (VSM); VECTOR SPACES; WEB CONTENTS; WEB DOCUMENT CLASSIFICATION; WEB DOCUMENTS;

CANNING; CLASSIFICATION (OF INFORMATION); CLASSIFIERS; DECISION MAKING; DECISION THEORY; DECISION TREES; GRAPH THEORY; HYBRID SENSORS; INFORMATION SERVICES; LEARNING SYSTEMS; MARKUP LANGUAGES; MATHEMATICAL MODELS; SEARCH ENGINES; TEXT PROCESSING; VECTORS; WORLD WIDE WEB;

INFORMATION RETRIEVAL SYSTEMS;

EID: 44649195119     PISSN: 08848173     EISSN: 1098111X     Source Type: Journal    
DOI: 10.1002/int.20290     Document Type: Article

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