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» Selective association rule generation
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ICTAI
2007
IEEE
15 years 10 months ago
Exploratory Quantitative Contrast Set Mining: A Discretization Approach
Contrast sets have been shown to be a useful tool for describing differences between groups. A contrast set is a set of association rules for which the antecedents describe distin...
Mondelle Simeon, Robert J. Hilderman
VLDB
2004
ACM
104views Database» more  VLDB 2004»
16 years 4 months ago
Retrieval effectiveness of an ontology-based model for information selection
Technology in the field of digital media generates huge amounts of nontextual information, audio, video, and images, along with more familiar textual information. The potential for...
Latifur Khan, Dennis McLeod, Eduard H. Hovy
IJCAI
2007
15 years 6 months ago
A Fully Connectionist Model Generator for Covered First-Order Logic Programs
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...
Sebastian Bader, Pascal Hitzler, Steffen Höll...
ML
2000
ACM
154views Machine Learning» more  ML 2000»
15 years 4 months ago
Lazy Learning of Bayesian Rules
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
Zijian Zheng, Geoffrey I. Webb
HICSS
2005
IEEE
164views Biometrics» more  HICSS 2005»
15 years 10 months ago
An Efficient Technique for Frequent Pattern Mining in Real-Time Business Applications
Association rule mining in real-time is of increasing thrust in many business applications. Applications such as e-commerce, recommender systems, supply-chain management and group...
Rajanish Dass, Ambuj Mahanti