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177
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KDD
2006
ACM
16 years 6 months ago
2006
ACM
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
161
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KDD
2006
ACM
16 years 6 months ago
2006
ACM
Outlier detection can uncover malicious behavior in fields like intrusion detection and fraud analysis. Although there has been a significant amount of work in outlier detection, ...
182
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KDD
2006
ACM
16 years 6 months ago
2006
ACM
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
182
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KDD
2005
ACM
16 years 6 months ago
2005
ACM
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
159
click to vote
KDD
2005
ACM
16 years 6 months ago
2005
ACM
Dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. A fundamental problem in dyadic data a...