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» Phenomenal Data Mining: From Data to Phenomena
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AAAI
1996
15 years 3 months ago
Post-Analysis of Learned Rules
Rule induction research implicitly assumes that after producing the rules from a dataset, these rules will be used directly by an expert system or a human user. In real-life appli...
Bing Liu, Wynne Hsu
KDD
2012
ACM
181views Data Mining» more  KDD 2012»
13 years 4 months ago
On "one of the few" objects
Objects with multiple numeric attributes can be compared within any “subspace” (subset of attributes). In applications such as computational journalism, users are interested i...
You Wu, Pankaj K. Agarwal, Chengkai Li, Jun Yang 0...
ICDM
2008
IEEE
401views Data Mining» more  ICDM 2008»
15 years 8 months ago
Graph OLAP: Towards Online Analytical Processing on Graphs
OLAP (On-Line Analytical Processing) is an important notion in data analysis. Recently, more and more graph or networked data sources come into being. There exists a similar need ...
Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han, Phil...
179
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MSR
2006
ACM
15 years 7 months ago
Predicting defect densities in source code files with decision tree learners
With the advent of open source software repositories the data available for defect prediction in source files increased tremendously. Although traditional statistics turned out t...
Patrick Knab, Martin Pinzger, Abraham Bernstein
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
15 years 3 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...