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ICDE
2008
IEEE
137views Database» more  ICDE 2008»
16 years 7 months ago
Stop Chasing Trends: Discovering High Order Models in Evolving Data
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
Shixi Chen, Haixun Wang, Shuigeng Zhou, Philip S. ...
161
Voted
COMPUTE
2010
ACM
15 years 10 months ago
Mining periodic-frequent patterns with maximum items' support constraints
The single minimum support (minsup) based frequent pattern mining approaches like Apriori and FP-growth suffer from“rare item problem”while extracting frequent patterns. That...
R. Uday Kiran, P. Krishna Reddy
VLDB
1999
ACM
224views Database» more  VLDB 1999»
15 years 10 months ago
Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering
Many applications require the clustering of large amounts of high-dimensional data. Most clustering algorithms, however, do not work e ectively and e ciently in highdimensional sp...
Alexander Hinneburg, Daniel A. Keim
CCS
2006
ACM
15 years 10 months ago
RoleMiner: mining roles using subset enumeration
Role engineering, the task of defining roles and associating permissions to them, is essential to realize the full benefits of the role-based access control paradigm. Essentially,...
Jaideep Vaidya, Vijayalakshmi Atluri, Janice Warne...
AI
2010
Springer
15 years 6 months ago
Understanding the scalability of Bayesian network inference using clique tree growth curves
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Ole J. Mengshoel