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» Mining Very Large Databases
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BNCOD
2003
127views Database» more  BNCOD 2003»
13 years 11 months ago
Performance Evaluation and Analysis of K-Way Join Variants for Association Rule Mining
Data mining aims at discovering important and previously unknown patterns from the dataset in the underlying database. Database mining performs mining directly on data stored in r...
P. Mishra, Sharma Chakravarthy
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
12 years 13 days ago
Sampling minimal frequent boolean (DNF) patterns
We tackle the challenging problem of mining the simplest Boolean patterns from categorical datasets. Instead of complete enumeration, which is typically infeasible for this class ...
Geng Li, Mohammed J. Zaki
ICDE
2004
IEEE
116views Database» more  ICDE 2004»
14 years 11 months ago
An Efficient Algorithm for Mining Frequent Sequences by a New Strategy without Support Counting
Mining sequential patterns in large databases is an important research topic. The main challenge of mining sequential patterns is the high processing cost due to the large amount ...
Ding-Ying Chiu, Yi-Hung Wu, Arbee L. P. Chen
DEXA
2004
Springer
190views Database» more  DEXA 2004»
14 years 3 months ago
On Efficient and Effective Association Rule Mining from XML Data
: In this paper, we propose a framework, called XAR-Miner, for mining ARs from XML documents efficiently and effectively. In XAR-Miner, raw XML data are first transformed to either...
Ji Zhang, Tok Wang Ling, Robert M. Bruckner, A. Mi...
KBS
2006
87views more  KBS 2006»
13 years 10 months ago
Predictive and comprehensible rule discovery using a multi-objective genetic algorithm
We present a multi-objective genetic algorithm for mining highly predictive and comprehensible classification rules from large databases. We emphasize predictive accuracy and comp...
Satchidananda Dehuri, Rajib Mall