Principles for mining summaries using objective measures of interestingness

Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI

Volumn 2000-January, Issue , 2000, Pages 72-81

  Hilderman, R J ^a   Hamilton, H J ^a  

^a UNIVERSITY OF REGINA   (Canada)

Author keywords

Area measurement; Computer science; Data mining; Databases; Environmental factors; Gain measurement; Information theory; Performance evaluation; Sensitivity analysis; Statistics

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; DATABASE SYSTEMS; GAIN MEASUREMENT; INFORMATION THEORY; SENSITIVITY ANALYSIS; STATISTICS;

AREA MEASUREMENT; DIVERSITY MEASURE; EFFECTIVE MEASURES; ENVIRONMENTAL FACTORS; INTERESTINGNESS; OBJECTIVE MEASURE; PERFORMANCE EVALUATION;

DATA MINING;

EID: 78149322412     PISSN: 10823409     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/TAI.2000.889848     Document Type: Conference Paper

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