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RCIS
2010
14 years 8 months ago
A Tree-based Approach for Efficiently Mining Approximate Frequent Itemsets
—The strategies for mining frequent itemsets, which is the essential part of discovering association rules, have been widely studied over the last decade. In real-world datasets,...
Jia-Ling Koh, Yi-Lang Tu
ICDM
2003
IEEE
125views Data Mining» more  ICDM 2003»
15 years 3 months ago
Clustering Item Data Sets with Association-Taxonomy Similarity
We explore in this paper the efficient clustering of item data. Different from those of the traditional data, the features of item data are known to be of high dimensionality and...
Ching-Huang Yun, Kun-Ta Chuang, Ming-Syan Chen
PAKDD
2004
ACM
121views Data Mining» more  PAKDD 2004»
15 years 3 months ago
Secure Association Rule Sharing
Abstract. The sharing of association rules is often beneficial in industry, but requires privacy safeguards. One may decide to disclose only part of the knowledge and conceal stra...
Stanley R. M. Oliveira, Osmar R. Zaïane, Y&uu...
AMAI
2007
Springer
14 years 10 months ago
Relational concept discovery in structured datasets
Relational datasets, i.e., datasets in which individuals are described both by their own features and by their relations to other individuals, arise from various sources such as d...
Marianne Huchard, Mohamed Rouane Hacene, Cyril Rou...
PAKDD
2005
ACM
128views Data Mining» more  PAKDD 2005»
15 years 3 months ago
A Two-Phase Algorithm for Fast Discovery of High Utility Itemsets
Traditional association rules mining cannot meet the demands arising from some real applications. By considering the different values of individual items as utilities, utility mini...
Ying Liu, Wei-keng Liao, Alok N. Choudhary