Legal question answering using ranking SVM and syntactic/semantic similarity

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9067, Issue , 2015, Pages 244-258

  Kim, Mi Young ^a   Xu, Ying ^a   Goebel, Randy ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

Information retrieval; Latent dirichlet allocation (LDA); Legal text mining; Question answering; Ranking SVM; Recognizing textual entailment

Indexed keywords

ARTIFICIAL INTELLIGENCE; CHARACTER RECOGNITION; DATA MINING; INFORMATION RETRIEVAL; NATURAL LANGUAGE PROCESSING SYSTEMS; QUERY PROCESSING; STATISTICS; SYNTACTICS; TEXT PROCESSING;

LATENT DIRICHLET ALLOCATIONS; LEGAL TEXTS; QUESTION ANSWERING; RANKING SVM; RECOGNIZING TEXTUAL ENTAILMENTS;

SEARCH ENGINES;

EID: 84945558111     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-662-48119-6_18     Document Type: Conference Paper

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