SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
Multi-dimensional sequential pattern mining
Proceedings of the tenth international conference on Information and knowledge management
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Constraint-Based Tutors: A Success Story
Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems
Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach
IEEE Transactions on Knowledge and Data Engineering
Closed Multidimensional Sequential Pattern Mining
ITNG '06 Proceedings of the Third International Conference on Information Technology: New Generations
Frequent Closed Sequence Mining without Candidate Maintenance
IEEE Transactions on Knowledge and Data Engineering
Using Knowledge Discovery Techniques to Support Tutoring in an Ill-Defined Domain
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Path-planning for autonomous training on robot manipulators in space
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
The cognitive tutor authoring tools (CTAT): preliminary evaluation of efficiency gains
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Learning task models in ill-defined domain using an hybrid knowledge discovery framework
Knowledge-Based Systems
FAST sequence mining based on sparse id-lists
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Elaborating analysis models with tool support
INTERACT'11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction - Volume Part IV
Modeling topic trends on the social web using temporal signatures
Proceedings of the twelfth international workshop on Web information and data management
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Domain experts should provide relevant domain knowledge to an Intelligent Tutoring System (ITS) so that it can guide a learner during problem-solving learning activities. However, for many ill-defined domains, the domain knowledge is hard to define explicitly. In previous works, we showed how sequential pattern mining can be used to extract a partial problem space from logged user interactions, and how it can support tutoring services during problem-solving exercises. This article describes an extension of this approach to extract a problem space that is richer and more adapted for supporting tutoring services. We combined sequential pattern mining with (1) dimensional pattern mining (2) time intervals, (3) the automatic clustering of valued actions and (4) closed sequences mining. Some tutoring services have been implemented and an experiment has been conducted in a tutoring system.