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» Efficient Frequent Pattern Mining in Relational Databases
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KDD
2003
ACM
135views Data Mining» more  KDD 2003»
14 years 8 months ago
Efficiently handling feature redundancy in high-dimensional data
High-dimensional data poses a severe challenge for data mining. Feature selection is a frequently used technique in preprocessing high-dimensional data for successful data mining....
Lei Yu, Huan Liu
KES
2004
Springer
14 years 1 months ago
FIT: A Fast Algorithm for Discovering Frequent Itemsets in Large Databases
Association rule mining is an important data mining problem that has been studied extensively. In this paper, a simple but Fast algorithm for Intersecting attribute lists using a ...
Jun Luo, Sanguthevar Rajasekaran
ICDM
2007
IEEE
150views Data Mining» more  ICDM 2007»
14 years 2 months ago
Connections between Mining Frequent Itemsets and Learning Generative Models
Frequent itemsets mining is a popular framework for pattern discovery. In this framework, given a database of customer transactions, the task is to unearth all patterns in the for...
Srivatsan Laxman, Prasad Naldurg, Raja Sripada, Ra...
WAIM
2004
Springer
14 years 1 months ago
Learning-Based Top-N Selection Query Evaluation over Relational Databases
A top-N selection query against a relation is to find the N tuples that satisfy the query condition the best but not necessarily completely. In this paper, we propose a new method ...
Liang Zhu, Weiyi Meng
IDEAS
2005
IEEE
99views Database» more  IDEAS 2005»
14 years 1 months ago
Distribution-Based Synthetic Database Generation Techniques for Itemset Mining
The resource requirements of frequent pattern mining algorithms depend mainly on the length distribution of the mined patterns in the database. Synthetic databases, which are used...
Ganesh Ramesh, Mohammed Javeed Zaki, William Mania...