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KDD
2009
ACM
163views Data Mining» more  KDD 2009»
14 years 10 months ago
Large-scale graph mining using backbone refinement classes
We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...
Andreas Maunz, Christoph Helma, Stefan Kramer
KDD
2009
ACM
239views Data Mining» more  KDD 2009»
14 years 10 months ago
Tell me something I don't know: randomization strategies for iterative data mining
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however...
Heikki Mannila, Kai Puolamäki, Markus Ojala, ...
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
14 years 10 months ago
Constant-factor approximation algorithms for identifying dynamic communities
We propose two approximation algorithms for identifying communities in dynamic social networks. Communities are intuitively characterized as "unusually densely knit" sub...
Chayant Tantipathananandh, Tanya Y. Berger-Wolf
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 10 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
KDD
2009
ACM
229views Data Mining» more  KDD 2009»
14 years 10 months ago
Relational learning via latent social dimensions
Social media such as blogs, Facebook, Flickr, etc., presents data in a network format rather than classical IID distribution. To address the interdependency among data instances, ...
Lei Tang, Huan Liu