Hierarchical bayesian models for collaborative tagging systems

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2009, Pages 728-733

  Bundschus, Markus ^a   Yu, Shipeng ^b   Tresp, Volker ^c   Rettinger, Achim ^d   Dejori, Mathaeus ^e   Kriegel, Hans Peter ^a  

^a UNIVERSITY OF MUNICH   (Germany)

^b CAD and Knowledge Solutions   (United States)

^c SIEMENS AG   (Germany)

^d TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^e SIEMENS CORPORATE RESEARCH   (United States)

Author keywords

Collaborative tagging; LDA; User modeling

Indexed keywords

COLLABORATIVE TAGGING; COMMON KNOWLEDGE; DATA COMPLEXITY; DEVELOPED MODEL; HIERARCHICAL BAYESIAN MODELS; INFORMATION EXTRACTION; LATENT DIRICHLET ALLOCATION; PROBABILISTIC APPROACHES; SEMANTIC DATA; USER INFORMATION; USER MODELING; USER-GENERATED CONTENT;

BAYESIAN NETWORKS; THESAURI; WEBSITES;

HIERARCHICAL SYSTEMS;

EID: 77951165602     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2009.121     Document Type: Conference Paper

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