Effective document clustering for large heterogeneous law firm collections

Proceedings of the International Conference on Artificial Intelligence and Law

Volumn , Issue , 2005, Pages 177-187

  Conrad, Jack G ^a   Al Kofahi, Khalid ^a   Zhao, Ying ^b   Karypis, George ^b  

^a Research and Development   (United States)

^b UNIVERSITY OF MINNESOTA   (United States)

Author keywords

Document clustering; Knowledgement management; Legal data; Taxonomy development

Indexed keywords

ALTERNATIVE APPROACH; AUTOMATED ASSISTANCE; CASE LAW; CLUSTERING APPROACH; COMPUTATIONAL RESOURCES; DOCUMENT CLUSTERING; EXTERNAL QUALITY; HARD CLUSTERING; HIER-ARCHICAL CLUSTERING; KNOWLEDGEMENT MANAGEMENT; LABELED DATA; LARGE DATABASE; LAW FIRM; LEGAL DOCUMENTS; MULTIPLE CLUSTERS; REMOTE ACCESS; SEMI-AUTOMATIC GENERATION; SOFT CLUSTERING; TEXT CLASSIFICATION; WORK PRODUCTS;

ARTIFICIAL INTELLIGENCE; INFORMATION RETRIEVAL; KNOWLEDGE MANAGEMENT; TAXONOMIES; TEXT PROCESSING;

CLUSTER ANALYSIS;

EID: 37749049420     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1165485.1165513     Document Type: Conference Paper

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