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» Mining Frequent Itemsets Using Support Constraints
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KDD
2002
ACM
189views Data Mining» more  KDD 2002»
14 years 8 months ago
Sequential PAttern mining using a bitmap representation
We introduce a new algorithm for mining sequential patterns. Our algorithm is especially efficient when the sequential patterns in the database are very long. We introduce a novel...
Jay Ayres, Jason Flannick, Johannes Gehrke, Tomi Y...
AUSAI
2001
Springer
13 years 11 months ago
Further Pruning for Efficient Association Rule Discovery
The Apriori algorithm's frequent itemset approach has become the standard approach to discovering association rules. However, the computation requirements of the frequent item...
Songmao Zhang, Geoffrey I. Webb
ICDT
2009
ACM
119views Database» more  ICDT 2009»
14 years 8 months ago
Analysis of sampling techniques for association rule mining
In this paper, we present a comprehensive theoretical analysis of the sampling technique for the association rule mining problem. Most of the previous works have concentrated only...
Venkatesan T. Chakaravarthy, Vinayaka Pandit, Yogi...
DAWAK
2004
Springer
13 years 11 months ago
PROWL: An Efficient Frequent continuity Mining Algorithm on Event Sequences
Mining association rule in event sequences is an important data mining problem with many applications. Most of previous studies on association rules are on mining intra-transaction...
Kuo-Yu Huang, Chia-Hui Chang, Kuo-Zui Lin
KDD
1999
ACM
220views Data Mining» more  KDD 1999»
13 years 11 months ago
Efficient Mining of Emerging Patterns: Discovering Trends and Differences
We introduce a new kind of patterns, called emerging patterns (EPs), for knowledge discovery from databases. EPs are defined as itemsets whose supports increase significantly from...
Guozhu Dong, Jinyan Li