On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
On the MSE robustness of batching estimators
Proceedings of the 33nd conference on Winter simulation
Domain-Specific Keyphrase Extraction
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
ELM-ART: An Intelligent Tutoring System on World Wide Web
ITS '96 Proceedings of the Third International Conference on Intelligent Tutoring Systems
Information Sciences: an International Journal
The effectiveness of automatic text summarization in mobile learning contexts
Computers & Education
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The research presented in this paper is an examination of the applicability of IUI techniques in an online e-learning environment. In particular we make use of user modeling techniques, information retrieval and extraction mechanisms and collaborative filtering methods. The domains of e-learning, web-based training and instruction and intelligent tutoring systems provide a challenging environment due to the large and diverse user population it entails. The overall system concentrates on utilizing a user modeling system to filter results as part of a collaborative document recommendation system. The goal of such a system is to actively seek out and recommend documents that will either encourage the users to expand their knowledge of a given topic or reinforce the knowledge which they already have. The system aims to recommend these documents in a non-intrusive manner with minimal user inconvenience, and attempts to do so by utilizing the Key Extraction Algorithm and automatically extracting queries, searching the web and filtering the search results. Users are encouraged to provide feedback about the resources and links they have viewed.