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ICDM
2007
IEEE
169views Data Mining» more  ICDM 2007»
14 years 13 days ago
Efficient Discovery of Frequent Approximate Sequential Patterns
We propose an efficient algorithm for mining frequent approximate sequential patterns under the Hamming distance model. Our algorithm gains its efficiency by adopting a "brea...
Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu
PAKDD
2004
ACM
199views Data Mining» more  PAKDD 2004»
14 years 1 months ago
Temporal Sequence Associations for Rare Events
In many real world applications, systematic analysis of rare events, such as credit card frauds and adverse drug reactions, is very important. Their low occurrence rate in large da...
Jie Chen, Hongxing He, Graham J. Williams, Huidong...
CIKM
2004
Springer
14 years 2 months ago
Scalable sequential pattern mining for biological sequences
Biosequences typically have a small alphabet, a long length, and patterns containing gaps (i.e., “don’t care”) of arbitrary size. Mining frequent patterns in such sequences ...
Ke Wang, Yabo Xu, Jeffrey Xu Yu
KDD
2007
ACM
176views Data Mining» more  KDD 2007»
14 years 9 months ago
Mining correlated bursty topic patterns from coordinated text streams
Previous work on text mining has almost exclusively focused on a single stream. However, we often have available multiple text streams indexed by the same set of time points (call...
Xuanhui Wang, ChengXiang Zhai, Xiao Hu, Richard Sp...
CIB
2002
100views more  CIB 2002»
13 years 8 months ago
Web-log Mining for Quantitative Temporal-Event Prediction
The web log data embed much of web users' browsing behavior. From the web logs, one can discover patterns that predict the users' future requests based on their current b...
Qiang Yang, Hui Wang, Wei Zhang