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ICDE
2009
IEEE
173views Database» more  ICDE 2009»
13 years 5 months ago
Efficient Mining of Closed Repetitive Gapped Subsequences from a Sequence Database
There is a huge wealth of sequence data available, for example, customer purchase histories, program execution traces, DNA, and protein sequences. Analyzing this wealth of data to ...
Bolin Ding, David Lo, Jiawei Han, Siau-Cheng Khoo
AUSDM
2007
Springer
131views Data Mining» more  AUSDM 2007»
14 years 1 months ago
A Bottom-Up Projection Based Algorithm for Mining High Utility Itemsets
Mining High Utility Itemsets from a transaction database is to find itemsests that have utility above a user-specified threshold. This problem is an extension of Frequent Itemset ...
Alva Erwin, Raj P. Gopalan, N. R. Achuthan
KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 7 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
ICCV
2007
IEEE
14 years 9 months ago
Discriminative Subsequence Mining for Action Classification
Recent approaches to action classification in videos have used sparse spatio-temporal words encoding local appearance around interesting movements. Most of these approaches use a ...
Sebastian Nowozin, Gökhan H. Bakir, Koji Tsud...
ICTAI
2003
IEEE
14 years 20 days ago
Parallel Mining of Maximal Frequent Itemsets from Databases
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Soon Myoung Chung, Congnan Luo