Learning with positive and unlabeled examples using topic-sensitive PLSA

IEEE Transactions on Knowledge and Data Engineering

Volumn 22, Issue 1, 2010, Pages 46-58

  Zhou, Ke ^a   Gui Rong, Xue ^a   Yang, Qiang ^b   Yu, Yong ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

Document classification.; Semisupervised learning; Topic sensitive probabilistic latent semantic analysis

Indexed keywords

CLASSIFICATION SYSTEM; CRITICAL PROBLEMS; DOCUMENT CLASSIFICATION; EXPERIMENTAL EVALUATION; ITERATIVE ALGORITHM; LOCAL OPTIMA; MACHINE-LEARNING; NEGATIVE EXAMPLES; NOVEL ALGORITHM; OBJECTIVE FUNCTIONS; OBSERVED DATA; PENALTY TERM; POSITIVE DATA; POSITIVE EXAMPLES; PROBABILISTIC LATENT SEMANTIC ANALYSIS; SEMI-SUPERVISED LEARNING; UNLABELED DATA; USERS' INTERESTS;

ALGORITHMS; EDUCATION; IMAGE RETRIEVAL; INFORMATION RETRIEVAL SYSTEMS; INFORMATION SERVICES; LEARNING SYSTEMS; SEMANTICS;

PROBLEM SOLVING;

EID: 72949090151     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2009.56     Document Type: Article

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