Help Desk Architecture for a U-Learning System Characterized by the Use of Probabilistic Reasoning-based Search of a Case Base

Y. Fujiwara, S. Abe, Y. Maeda, and H. Yoshida (Japan)


and cases stored in a case base, using a Bayesian network. The Noisy-or rule is used to simplify the setting of the conditional probabil ity between a key word node and a case node, and also the computation needed to select candidate cases. We have developed an experimental case base that contains typical Q&As likely to occur in a u-learning system, and examined the performance of this indexing method. It is shown that the use of a history database to tune the index parameters can drama


This paper proposes an architecture for a help desk for a u-learning system. The architecture is characterized by the use of a case base search based on probabilistic reasoning. This case base search method uses indices that represent the relationships between

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