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KDD
2012
ACM
187views Data Mining» more  KDD 2012»
13 years 7 months ago
Sampling minimal frequent boolean (DNF) patterns
We tackle the challenging problem of mining the simplest Boolean patterns from categorical datasets. Instead of complete enumeration, which is typically infeasible for this class ...
Geng Li, Mohammed J. Zaki
KDD
2009
ACM
182views Data Mining» more  KDD 2009»
16 years 5 months ago
Scalable graph clustering using stochastic flows: applications to community discovery
Algorithms based on simulating stochastic flows are a simple and natural solution for the problem of clustering graphs, but their widespread use has been hampered by their lack of...
Venu Satuluri, Srinivasan Parthasarathy
ICDM
2010
IEEE
122views Data Mining» more  ICDM 2010»
15 years 3 months ago
Interesting Subset Discovery and Its Application on Service Processes
Various real-life datasets can be viewed as a set of records consisting of attributes explaining the records and set of measures evaluating the records. In this paper, we address t...
Maitreya Natu, Girish Keshav Palshikar
SDM
2007
SIAM
130views Data Mining» more  SDM 2007»
15 years 6 months ago
Towards Attack-Resilient Geometric Data Perturbation
Data perturbation is a popular technique for privacypreserving data mining. The major challenge of data perturbation is balancing privacy protection and data quality, which are no...
Keke Chen, Gordon Sun, Ling Liu
ICDM
2007
IEEE
133views Data Mining» more  ICDM 2007»
15 years 11 months ago
Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval
Most topic models, such as latent Dirichlet allocation, rely on the bag-of-words assumption. However, word order and phrases are often critical to capturing the meaning of text in...
Xuerui Wang, Andrew McCallum, Xing Wei