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» CURE: An Efficient Clustering Algorithm for Large Databases
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ICDE
2007
IEEE
126views Database» more  ICDE 2007»
16 years 1 months ago
Efficient Approximation Algorithms for Repairing Inconsistent Databases
We consider the problem of repairing a database that is inconsistent wrt a set of integrity constraints by updating numerical values. In particular, we concentrate on denial integ...
Andrei Lopatenko, Loreto Bravo
79
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AAAI
2008
15 years 2 months ago
Visualization of Large-Scale Weighted Clustered Graph: A Genetic Approach
In this paper, a bottom-up hierarchical genetic algorithm is proposed to visualize clustered data into a planar graph. To achieve global optimization by accelerating local optimiz...
Jiayu Zhou, Youfang Lin, Xi Wang
SIGMOD
2004
ACM
140views Database» more  SIGMOD 2004»
15 years 12 months ago
Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering
Mining informative patterns from very large, dynamically changing databases poses numerous interesting challenges. Data summarizations (e.g., data bubbles) have been proposed to c...
Corrine Cheng, Jörg Sander, Samer Nassar
ICDE
2002
IEEE
138views Database» more  ICDE 2002»
16 years 1 months ago
Efficient Temporal Join Processing Using Indices
We examine the problem of processing temporal joins in the presence of indexing schemes. Previous work on temporal joins has concentrated on non-indexed relations which were fully...
Donghui Zhang, Vassilis J. Tsotras, Bernhard Seege...
SIGMOD
2000
ACM
212views Database» more  SIGMOD 2000»
15 years 4 months ago
SQLEM: Fast Clustering in SQL using the EM Algorithm
Clustering is one of the most important tasks performed in Data Mining applications. This paper presents an e cient SQL implementation of the EM algorithm to perform clustering in...
Carlos Ordonez, Paul Cereghini