Latent graphical models for quantifying and predicting patent quality

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2011, Pages 1145-1153

  Liu, Yan ^a   Hseuh, Pei Yun ^b   Lawrence, Rick ^b   Meliksetian, Steve ^b   Perlich, Claudia ^b   Veen, Alejandro ^b  

^a University of Southern California   (United States)

^b IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

Graphical models; Measurement models; Text mining

Indexed keywords

DATA MINING; NATURAL LANGUAGE PROCESSING SYSTEMS; PATENTS AND INVENTIONS;

GRAPHICAL MODEL; HIGH QUALITY; LANGUAGE PROCESSING TECHNIQUES; LEXICAL FEATURES; MEASUREMENT MODEL; NATURAL LANGUAGES; OBJECTIVE MODELS; QUALITY MEASURES; STRONG DEMAND; TEXT-MINING;

GRAPHIC METHODS;

EID: 80052665320     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2020408.2020586     Document Type: Conference Paper

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