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» Mining evolving data streams for frequent patterns
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KDD
2004
ACM
210views Data Mining» more  KDD 2004»
15 years 10 months ago
Web usage mining based on probabilistic latent semantic analysis
The primary goal of Web usage mining is the discovery of patterns in the navigational behavior of Web users. Standard approaches, such as clustering of user sessions and discoveri...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
15 years 10 months ago
Characteristic relational patterns
Research in relational data mining has two major directions: finding global models of a relational database and the discovery of local relational patterns within a database. While...
Arne Koopman, Arno Siebes
KDD
2007
ACM
249views Data Mining» more  KDD 2007»
15 years 10 months ago
The minimum consistent subset cover problem and its applications in data mining
In this paper, we introduce and study the Minimum Consistent Subset Cover (MCSC) problem. Given a finite ground set X and a constraint t, find the minimum number of consistent sub...
Byron J. Gao, Martin Ester, Jin-yi Cai, Oliver Sch...
KDD
2006
ACM
113views Data Mining» more  KDD 2006»
15 years 10 months ago
A new efficient probabilistic model for mining labeled ordered trees
Mining frequent patterns is a general and important issue in data mining. Complex and unstructured (or semi-structured) datasets have appeared in major data mining applications, i...
Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhi...
KDD
2006
ACM
109views Data Mining» more  KDD 2006»
15 years 10 months ago
Extracting redundancy-aware top-k patterns
Observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. The significance...
Dong Xin, Hong Cheng, Xifeng Yan, Jiawei Han