| Document Date: 2010-04-02 16:42:57
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City Contraint / Constraint / / Company Intelligent Tutoring Systems / Intelligent Educational Software / Artificial Intelligence & Expert Systems / Interactive / / Country France / Canada / / Currency pence / / / Facility International Space Station / / IndustryTerm sequential pattern mining algorithm / proposed data mining framework / buggy solutions / plan recognition algorithm / sequential pattern algorithm / data mining framework / sequential pattern mining / important tutoring services / learner solutions / data mining approach / key tutoring services / buggy solution / domain knowledge mining / mining / tutoring services / elaborated tutoring services / user solutions / select sucessful solutions / supported tutoring services / main tutoring services / approximate solutions / arguable solutions / / Organization GDAC / / Person Mikael Watrelot / P. Songram / V / Severin Vigot / K. Ashley / V / Blaise Pascal / Engelbert Mephu / / Position aforementioned path planner / Analyzing Student-Tutor / special path-planner / Semi-Automated Tutor / The Cognitive Tutor / / Technology expert system / sequential pattern mining algorithm / Knowledge Management / Java / Information Technology / sequential pattern algorithm / plan recognition algorithm / data mining / Machine Learning / simulation / / URL http /
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Exploiting Partial Problem Spaces Learned from Users‟ Interactions to Provide Key Tutoring Services in Procedural and IllDefined Domains Philippe Fournier-Viger1, Roger Nkambou1 and Engelbert Mephu Nguifo2 Université