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» A Pattern Mining Approach Using QVT
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ICDM
2008
IEEE
120views Data Mining» more  ICDM 2008»
15 years 8 months ago
Predicting Future Decision Trees from Evolving Data
Recognizing and analyzing change is an important human virtue because it enables us to anticipate future scenarios and thus allows us to act pro-actively. One approach to understa...
Mirko Böttcher, Martin Spott, Rudolf Kruse
KDD
2012
ACM
190views Data Mining» more  KDD 2012»
13 years 4 months ago
Multi-label hypothesis reuse
Multi-label learning arises in many real-world tasks where an object is naturally associated with multiple concepts. It is well-accepted that, in order to achieve a good performan...
Sheng-Jun Huang, Yang Yu, Zhi-Hua Zhou
KDD
2004
ACM
103views Data Mining» more  KDD 2004»
16 years 2 months ago
An objective evaluation criterion for clustering
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
Arindam Banerjee, John Langford
ICDM
2006
IEEE
193views Data Mining» more  ICDM 2006»
15 years 8 months ago
Local Correlation Tracking in Time Series
We address the problem of capturing and tracking local correlations among time evolving time series. Our approach is based on comparing the local auto-covariance matrices (via the...
Spiros Papadimitriou, Jimeng Sun, Philip S. Yu
AIED
2009
Springer
14 years 11 months ago
Exploiting Partial Problem Spaces Learned from Users' Interactions to Provide Key Tutoring Services in Procedural and Ill-Define
In previous works, we showed how sequential pattern mining can be used to extract a partial problem space from logged user interactions for a procedural and ill-defined domain wher...
Philippe Fournier-Viger, Roger Nkambou, Engelbert ...