Mining fine grained opinions by using probabilistic models and domain knowledge

Proceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010

Volumn 1, Issue , 2010, Pages 358-365

  Miao, Qingliang ^a   Li, Qiudan ^a   Zeng, Daniel ^b  

^a INSTITUTE OF AUTOMATION   (China)

^b UNIVERSITY OF ARIZONA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL APPROACH; CONDITIONAL RANDOM FIELD; DATA SOURCE; DOMAIN KNOWLEDGE; DOMAIN SPECIFIC; EXPLOSIVE GROWTH; FINE GRAINED; INDEPENDENT TASKS; OPINION EXTRACTION; OPINION MINING; PROBABILISTIC MODELS; PRODUCT FEATURE; REAL-WORLD DATASETS; SEMI-STRUCTURED; SEQUENCE LABELING; UNIFIED PROCESS; USER-GENERATED CONTENT;

FEATURE EXTRACTION;

EID: 78649861656     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WI-IAT.2010.193     Document Type: Conference Paper

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