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IS
2007
13 years 10 months ago
Discovering frequent geometric subgraphs
As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the req...
Michihiro Kuramochi, George Karypis
ICDM
2009
IEEE
153views Data Mining» more  ICDM 2009»
13 years 7 months ago
A New Clustering Algorithm Based on Regions of Influence with Self-Detection of the Best Number of Clusters
Clustering methods usually require to know the best number of clusters, or another parameter, e.g. a threshold, which is not ever easy to provide. This paper proposes a new graph-b...
Fabrice Muhlenbach, Stéphane Lallich
WSDM
2012
ACM
245views Data Mining» more  WSDM 2012»
12 years 5 months ago
The early bird gets the buzz: detecting anomalies and emerging trends in information networks
In this work we propose a novel approach to anomaly detection in streaming communication data. We first build a stochastic model for the system based on temporal communication pa...
Brian Thompson
SDM
2009
SIAM
160views Data Mining» more  SDM 2009»
14 years 7 months ago
Discovering Substantial Distinctions among Incremental Bi-Clusters.
A fundamental task of data analysis is comprehending what distinguishes clusters found within the data. We present the problem of mining distinguishing sets which seeks to find s...
Faris Alqadah, Raj Bhatnagar
ICDM
2006
IEEE
107views Data Mining» more  ICDM 2006»
14 years 4 months ago
Improving Grouped-Entity Resolution Using Quasi-Cliques
The entity resolution (ER) problem, which identifies duplicate entities that refer to the same real world entity, is essential in many applications. In this paper, in particular,...
Byung-Won On, Ergin Elmacioglu, Dongwon Lee, Jaewo...