Constrained information-theoretic tripartite graph clustering to identify semantically similar relations

IJCAI International Joint Conference on Artificial Intelligence

Volumn 2015-January, Issue , 2015, Pages 3882-3889

  Wang, Chenguang ^a   Song, Yangqiu ^b   Roth, Dan ^b   Wang, Chi ^c   Han, Jiawei ^b   Ji, Heng ^d   Zhang, Ming ^a  

^a PEKING UNIVERSITY   (China)

^b University of Illinois at Urbana Champaign   (United States)

^c MICROSOFT RESEARCH   (United States)

^d RENSSELAER POLYTECHNIC INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATA MINING; INFORMATION ANALYSIS; INFORMATION RETRIEVAL; INFORMATION THEORY; KNOWLEDGE BASED SYSTEMS; SUPERVISED LEARNING;

CANNOT LINKS; CLUSTERING RESULTS; KNOWLEDGE BASE; KNOWLEDGE BASIS; RELATION EXPRESSION; SEMI- SUPERVISED LEARNING; SIDE INFORMATION; TRIPARTITE GRAPHS;

CLUSTERING ALGORITHMS;

EID: 84949845756     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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