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KDD
2004
ACM
148views Data Mining» more  KDD 2004»
16 years 6 months ago
Interestingness of frequent itemsets using Bayesian networks as background knowledge
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Szymon Jaroszewicz, Dan A. Simovici
EDM
2009
105views Data Mining» more  EDM 2009»
15 years 3 months ago
Subspace Clustering of Skill Mastery: Identifying Skills that Separate Students
Abstract. In educational research, a fundamental goal is identifying which skills students have mastered, which skills they have not, and which skills they are in the process of ma...
Rebecca Nugent, Elizabeth Ayers, Nema Dean
PST
2008
15 years 7 months ago
Utility of Knowledge Extracted from Unsanitized Data when Applied to Sanitized Data
Knowledge discovery systems extract knowledge from data that can be used for making prediction about incomplete data items. Utility is a measure of the usefulness of the discovere...
Michal Sramka, Reihaneh Safavi-Naini, Jörg De...
EDM
2009
153views Data Mining» more  EDM 2009»
15 years 3 months ago
Automatic Detection of Student Mental Models During Prior Knowledge Activation in MetaTutor
This paper presents several methods to automatically detecting students' mental models in MetaTutor, an intelligent tutoring system that teaches students self-regulatory proce...
Vasile Rus, Mihai C. Lintean, Roger Azevedo
CIKM
2005
Springer
15 years 11 months ago
Opportunity map: a visualization framework for fast identification of actionable knowledge
Data mining techniques frequently find a large number of patterns or rules, which make it very difficult for a human analyst to interpret the results and to find the truly interes...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Weimin Xia...