Modeling interestingness of streaming association rules as a benefit-maximizing classification problem

Knowledge-Based Systems

Volumn 22, Issue 1, 2009, Pages 85-99

  Aydin, Tolga ^a   Güvenir, Halil Altay ^a  

^a BILKENT UNIVERSITY   (Turkey)

Author keywords

Classification learning; Data mining; Incremental learning; Interestingness learning

Indexed keywords

ASSOCIATION RULES; ASSOCIATIVE PROCESSING; DATA MINING; DECISION SUPPORT SYSTEMS; EDUCATION; INFORMATION MANAGEMENT; KETONES; LEARNING SYSTEMS;

APRIORI ALGORITHMS; ASSOCIATION RULE MININGS; CLASSIFICATION LEARNING; CLASSIFICATION SCHEMES; CONCEPT DESCRIPTIONS; DO-MAINS; DOMAIN EXPERTS; FIXED PERIODS; HUMAN EXPERTS; INCREMENTAL LEARNING; INTERESTINGNESS; INTERESTINGNESS LEARNING; MARKET BASKETS; POST-PROCESSING; REAL MARKETS; RULE LEARNING ALGORITHMS; RULE LEARNINGS; RULE SELECTIONS; TARGET FEATURES; TYPICAL APPLICATIONS; USER INTERACTIVITY;

LEARNING ALGORITHMS;

EID: 56649123399     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2008.07.003     Document Type: Article

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