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» Interpretations of Association Rules by Granular Computing
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ICDM
2003
IEEE
126views Data Mining» more  ICDM 2003»
14 years 4 months ago
Interpretations of Association Rules by Granular Computing
This paper presents interpretations for association rules. It first introduces Pawlak’s method, and the corresponding algorithm of finding decision rules (a kind of association ...
Yuefeng Li, Ning Zhong
RSEISP
2007
Springer
14 years 5 months ago
Interpreting Low and High Order Rules: A Granular Computing Approach
The main objective of this paper is to provide a granular computing based interpretation of rules representing two levels of knowledge. This is done by adopting and adapting the de...
Yiyu Yao, Bing Zhou, Yaohua Chen
SDM
2007
SIAM
146views Data Mining» more  SDM 2007»
14 years 7 days ago
ROAM: Rule- and Motif-Based Anomaly Detection in Massive Moving Object Data Sets
With recent advances in sensory and mobile computing technology, enormous amounts of data about moving objects are being collected. One important application with such data is aut...
Xiaolei Li, Jiawei Han, Sangkyum Kim, Hector Gonza...
ICSE
1993
IEEE-ACM
14 years 2 months ago
Rule-Based Approach to Computing Module Cohesion
Stevens, Myers, and Constantine introduced the notion of cohesion, an ordinal scale of seven levels that describes the degree to which the actions performed by a module contribute...
Arun Lakhotia
SIGKDD
2002
83views more  SIGKDD 2002»
13 years 10 months ago
Towards Effective and Interpretable Data Mining by Visual Interaction
The primary aim of most data mining algorithms is to facilitate the discovery of concise and interpretable information from large amounts of data. However, many of the current for...
Charu C. Aggarwal