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» On the Complexity of Mining Association Rules
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KDD
1997
ACM
154views Data Mining» more  KDD 1997»
14 years 9 days ago
Autonomous Discovery of Reliable Exception Rules
This paper presents an autonomous algorithm for discovering exception rules from data sets. An exception rule, which is defined as a deviational pattern to a well-known fact, exhi...
Einoshin Suzuki
HICSS
2005
IEEE
164views Biometrics» more  HICSS 2005»
14 years 2 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
DAWAK
2010
Springer
13 years 10 months ago
Mining Closed Itemsets in Data Stream Using Formal Concept Analysis
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
Anamika Gupta, Vasudha Bhatnagar, Naveen Kumar
ADMA
2010
Springer
248views Data Mining» more  ADMA 2010»
13 years 6 months ago
Classification Inductive Rule Learning with Negated Features
This paper reports on an investigation to compare a number of strategies to include negated features within the process of Inductive Rule Learning (IRL). The emphasis is on generat...
Stephanie Chua, Frans Coenen, Grant Malcolm
BTW
1999
Springer
145views Database» more  BTW 1999»
14 years 1 months ago
A Multi-Tier Architecture for High-Performance Data Mining
Data mining has been recognised as an essential element of decision support, which has increasingly become a focus of the database industry. Like all computationally expensive data...
Ralf Rantzau, Holger Schwarz