A conditional random field for discriminatively-trained finite-state string edit distance

Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence, UAI 2005

Volumn , Issue , 2005, Pages 388-395

  McCallum, Andrew ^a   Bellare, Kedar ^a   Pereira, Fernando ^b  

^a Biologically Inspired Neural and Dynamical Systems Laboratory   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; IMAGE SEGMENTATION; RANDOM PROCESSES;

BIOLOGICAL SEQUENCE ANALYSIS; CONDITIONAL RANDOM FIELD; EDIT DISTANCE; GENERATIVE MODEL; NEGATIVE INSTANCES; OBJECT IDENTITY; SEQUENCE SIMILARITY; TRAINING DATA;

DATA MINING;

EID: 44849098451     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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