A personal news agent that talks, learns and explains
Proceedings of the third annual conference on Autonomous Agents
An adaptive algorithm for learning changes in user interests
Proceedings of the eighth international conference on Information and knowledge management
Learning to recommend from positive evidence
Proceedings of the 5th international conference on Intelligent user interfaces
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
IEEE Transactions on Knowledge and Data Engineering
Automatic identification of user interest for personalized search
Proceedings of the 15th international conference on World Wide Web
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
An adaptive system for the personalized access to news
AI Communications
Open user profiles for adaptive news systems: help or harm?
Proceedings of the 16th international conference on World Wide Web
The adaptive web
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It is very difficult for blind and visually-impaired people getting information from the outside world. In this paper, we propose an adaptive Web news recommendation system named EagleRadio, designed for blind man and supports pervasive access using terminals. EagleRadio offers natural and user-friendly interface. News stories from different topics are read via a speech synthesizer to users and they can use commands to navigate inside the news space. Based on the analyzing of user’s listening history, adaptive topic navigation and news recommendation methods help users reaching relevant topics quickly and push the most relevant news to them. Finally, we evaluate the proposed algorithms and quantify the effect of EagleRadio from a user’s perspective.