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» Mining Very Large Databases
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216
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ICDE
1999
IEEE
94views Database» more  ICDE 1999»
16 years 5 months ago
Scalable Trigger Processing
Current database trigger systems have extremely limited scalability. This paper proposes a way to develop a truly scalable trigger system. Scalability to large numbers of trigger...
Eric N. Hanson, Chris Carnes, Lan Huang, Mohan Kon...
140
Voted
ICDM
2007
IEEE
173views Data Mining» more  ICDM 2007»
15 years 10 months ago
Sparse Word Graphs: A Scalable Algorithm for Capturing Word Correlations in Topic Models
Statistical topic models such as the Latent Dirichlet Allocation (LDA) have emerged as an attractive framework to model, visualize and summarize large document collections in a co...
Ramesh Nallapati, Amr Ahmed, William W. Cohen, Eri...
145
Voted
ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
15 years 9 months ago
Fast On-line Kernel Learning for Trees
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
131
Voted
SDM
2010
SIAM
182views Data Mining» more  SDM 2010»
15 years 5 months ago
HCDF: A Hybrid Community Discovery Framework
We introduce a novel Bayesian framework for hybrid community discovery in graphs. Our framework, HCDF (short for Hybrid Community Discovery Framework), can effectively incorporate...
Keith Henderson, Tina Eliassi-Rad, Spiros Papadimi...
120
Voted
SDM
2007
SIAM
73views Data Mining» more  SDM 2007»
15 years 5 months ago
Sketching Landscapes of Page Farms
The Web is a very large social network. It is important and interesting to understand the “ecology” of the Web: the general relations of Web pages to their environment. The un...
Bin Zhou 0002, Jian Pei