Abstract
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.
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Quarteroni, S., Manandhar, S. (2007). User Modelling for Personalized Question Answering. In: Basili, R., Pazienza, M.T. (eds) AI*IA 2007: Artificial Intelligence and Human-Oriented Computing. AI*IA 2007. Lecture Notes in Computer Science(), vol 4733. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74782-6_34
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DOI: https://doi.org/10.1007/978-3-540-74782-6_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74781-9
Online ISBN: 978-3-540-74782-6
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