Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
Collaborative interface agents
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
KEA: practical automatic keyphrase extraction
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Scaling question answering to the Web
Proceedings of the 10th international conference on World Wide Web
Empirical Evaluation of User Models and User-Adapted Systems
User Modeling and User-Adapted Interaction
User Modeling and User-Adapted Interaction
Improving User Modelling with Content-Based Techniques
UM '01 Proceedings of the 8th International Conference on User Modeling 2001
Preface to Special Issue on User Modeling for Web Information Retrieval
User Modeling and User-Adapted Interaction
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Personalizing search via automated analysis of interests and activities
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Implicit user modeling for personalized search
Proceedings of the 14th ACM international conference on Information and knowledge management
An adaptive system for the personalized access to news
AI Communications
Incorporating user models in question answering to improve readability
KRAQ '06 Proceedings of the Workshop KRAQ'06 on Knowledge and Reasoning for Language Processing
Answering contextual questions based on ontologies and question templates
Frontiers of Computer Science in China
Assessing user-specific difficulty of documents
Information Processing and Management: an International Journal
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In this paper, we address the problem of personalization in question answering (QA). We describe the personalization component of YourQA, our web-based QA system, which creates individual models of users based on their reading level and interests.First, we explain how user models are dynamically created, saved and updated to filter and re-rank the answers. Then, we focus on how the user's interests are used in YourQA. Finally, we introduce a methodology for user-centered evaluation of personalized QA. Our results show a significant improvement in the user's satisfaction when their profiles are used to personalize answers.