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» Efficient Frequent Itemsets Mining by Sampling
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ICDE
2005
IEEE
146views Database» more  ICDE 2005»
15 years 10 months ago
Mining Evolving Customer-Product Relationships in Multi-Dimensional Space
Previous work on mining transactional database has focused primarily on mining frequent itemsets, association rules, and sequential patterns. However, interesting relationships be...
Xiaolei Li, Jiawei Han, Xiaoxin Yin, Dong Xin
CIB
2004
57views more  CIB 2004»
14 years 9 months ago
Identifying Global Exceptional Patterns in Multi-database Mining
In multi-database mining, there can be many local patterns (frequent itemsets or association rules) in each database. At the end of multi-database mining, it is necessary to analyz...
Chengqi Zhang, Meiling Liu, Wenlong Nie, Shichao Z...
82
Voted
KDD
2006
ACM
183views Data Mining» more  KDD 2006»
15 years 9 months ago
Discovering interesting patterns through user's interactive feedback
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (i.e., frequent patterns) h...
Dong Xin, Xuehua Shen, Qiaozhu Mei, Jiawei Han
HICSS
2003
IEEE
171views Biometrics» more  HICSS 2003»
15 years 2 months ago
Improving the Efficiency of Interactive Sequential Pattern Mining by Incremental Pattern Discovery
The discovery of sequential patterns, which extends beyond frequent item-set finding of association rule mining, has become a challenging task due to its complexity. Essentially, ...
Ming-Yen Lin, Suh-Yin Lee
166
Voted
ICDE
2000
IEEE
112views Database» more  ICDE 2000»
15 years 10 months ago
DEMON: Mining and Monitoring Evolving Data
Data mining algorithms have been the focus of much research recently. In practice, the input data to a data mining process resides in a large data warehouse whose data is kept up-...
Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishn...