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» Approximate Association Rule Mining
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DAWAK
2010
Springer
13 years 11 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 8 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
JDWM
2010
139views more  JDWM 2010»
13 years 8 months ago
Mining Frequent Generalized Patterns for Web Personalization in the Presence of Taxonomies
The Web is a continuously evolving environment, since its content is updated on a regular basis. As a result, the traditional usagebased approach to generate recommendations that ...
Panagiotis Giannikopoulos, Iraklis Varlamis, Magda...
BTW
1999
Springer
145views Database» more  BTW 1999»
14 years 2 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
CORR
2010
Springer
279views Education» more  CORR 2010»
13 years 10 months ago
Mining Frequent Itemsets Using Genetic Algorithm
In general frequent itemsets are generated from large data sets by applying association rule mining algorithms like Apriori, Partition, Pincer-Search, Incremental, Border algorithm...
Soumadip Ghosh, Sushanta Biswas, Debasree Sarkar, ...