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KDD
1998
ACM
118views Data Mining» more  KDD 1998»
14 years 2 months ago
A Belief-Driven Method for Discovering Unexpected Patterns
Several pattern discovery methods proposed in the data mining literature have the drawbacks that they discover too many obvious or irrelevant patterns and that they do not leverag...
Balaji Padmanabhan, Alexander Tuzhilin
KDD
1997
ACM
96views Data Mining» more  KDD 1997»
14 years 2 months ago
Using General Impressions to Analyze Discovered Classification Rules
One of the important problems in data mining is the evaluation of subjective interestingness of the discovered rules. Past research has found that in many real-life applications i...
Bing Liu, Wynne Hsu, Shu Chen
CIKM
2009
Springer
14 years 2 months ago
Multidimensional political spectrum identification and analysis
In this work, we show the importance of multidimensional opinion representation in the political context combining domain knowledge and results from principal component analysis. ...
Leilei Zhu, Prasenjit Mitra
AUSDM
2006
Springer
118views Data Mining» more  AUSDM 2006»
14 years 2 months ago
Efficiently Identifying Exploratory Rules' Significance
How to efficiently discard potentially uninteresting rules in exploratory rule discovery is one of the important research foci in data mining. Many researchers have presented algor...
Shiying Huang, Geoffrey I. Webb
KDD
2010
ACM
287views Data Mining» more  KDD 2010»
14 years 9 days ago
Designing efficient cascaded classifiers: tradeoff between accuracy and cost
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...
Vikas C. Raykar, Balaji Krishnapuram, Shipeng Yu