Incremental and interactive sequence mining
Proceedings of the eighth international conference on Information and knowledge management
Discovery of Interesting Usage Patterns from Web Data
WEBKDD '99 Revised Papers from the International Workshop on Web Usage Analysis and User Profiling
Semantic networks -based teachable agents in an educational game
WSEAS Transactions on Computers
Teachable characters: semantic neural networks in game AI
NN'09 Proceedings of the 10th WSEAS international conference on Neural networks
Self-organizing content management with semantic neural networks
NN'09 Proceedings of the 10th WSEAS international conference on Neural networks
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Based on our previous work [3], learning patterns can be discovered and recommend to the learners. This paper extends the proposed problem to handle the questionable mining results. According to the learning patterns are discovered by using learning histories. It may be happened whenever the learners have ineffective learning behaviors, and we define them as questionable mining results. These ineffective behaviors may induce the bias suggestions. Therefore, we propose a candidate sequence set generation process to take care the stumble learning behavior.