Interest Derivation through Keywords
EUROMICRO '05 Proceedings of the 31st EUROMICRO Conference on Software Engineering and Advanced Applications
Use of contextualized attention metadata for ranking and recommending learning objects
CAMA '06 Proceedings of the 1st international workshop on Contextualized attention metadata: collecting, managing and exploiting of rich usage information
Utilizing vector space models for user modeling within e-learning environments
Computers & Education
Modeling user multiple interests by an improved GCS approach
Expert Systems with Applications: An International Journal
Modeling human behavior in user-adaptive systems: Recent advances using soft computing techniques
Expert Systems with Applications: An International Journal
Information Systems Frontiers
Keyword clustering for user interest profiling refinement within paper recommender systems
Journal of Systems and Software
Automated user modeling for personalized digital libraries
International Journal of Information Management: The Journal for Information Professionals
| Hi-index | 0.00 |
A prototype system for the fine-grained filtering of news items has been developed and a pilot test has been conducted. The system is based on an adaptive user model that integrates stereotypes and artificial neural networks. The stereotypes are based on newspaper sections and sub-sections, along with editor specified and user specified keywords. Eight subjects trained the system over six days of news papers (986 news items) and then tested the system on a seventh day (171 news items). Five users were simply asked to 'read the news' while three users developed 'corporate' profiles with explicit information needs. The evaluations suggests that such an integrated adaptive user model did, in fact, reflect the difference between the two different types of task. In both cases, the results also reflect the quality of the training of the adaptive neural network by the user in creating the user profile.