Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Proceedings of the 6th international conference on Intelligent user interfaces
User Modeling and User-Adapted Interaction
Learning implicit user interest hierarchy for context in personalization
Proceedings of the 8th international conference on Intelligent user interfaces
Dynamic User Model Construction with Bayesian Networks for Intelligent Information Queries
Proceedings of the Twelfth International Florida Artificial Intelligence Research Society Conference
Support for B2B E-Contracting - The Process Perspective
BASYS '02 Proceedings of the IFIP TC5/WG5.3 Fifth IFIP/IEEE International Conference on Information Technology for Balanced Automation Systems in Manufacturing and Services: Knowledge and Technology Integration in Production and Services: Balancing Knowledge in Product and Service Life Cycle
AHA! The adaptive hypermedia architecture
Proceedings of the fourteenth ACM conference on Hypertext and hypermedia
"Pluggable" user models for adaptive hypermedia in education
Proceedings of the fourteenth ACM conference on Hypertext and hypermedia
Evaluating adaptive hypermedia authoring while teaching adaptive systems
Proceedings of the 2004 ACM symposium on Applied computing
Predicting user preferences: from semantic to pragmatic metrics of Web navigation behavior
Dutch HCI '04 Proceedings of the conference on Dutch directions in HCI
Learner profile management for collaborating adaptive eLearning applications
Proceedings of the joint international workshop on Adaptivity, personalization & the semantic web
Evaluating Bayesian networks' precision for detecting students' learning styles
Computers & Education
User modeling in a distributed e-learning architecture
UM'05 Proceedings of the 10th international conference on User Modeling
Let's see how efficient open source LMSs can be and why
International Journal of Technology Enhanced Learning
A hybrid fuzzy-based personalized recommender system for telecom products/services
Information Sciences: an International Journal
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Over the past two decades, great research efforts have been made towards the personalization of e-learning platforms. This feature increases remarkably the quality of the provided learning services, since the users' special needs and capabilities are respected. The idea of predicting the users' preferences and adapting the e-learning platform accordingly is the focal point of this paper. In particular, this paper starts with the main requirements of an advanced e-learning system, explains the way a user navigates in such a system, presents the architecture of a corresponding e-learning system and describes its main components. Research is focused on the User Model component, its role in the e-learning system and the parameters that comprise it. In this context, Bayesian Networks are used as a tool for the encoding, learning and reasoning of probabilistic relationships, with the aim to effectively predict user preferences. In support of this vision, four different scenarios are presented, in order to test the way Bayesian Networks apply in the e-learning field.