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Most question answering and information retrieval systems are insensitive to different users' needs and preferences, as well as their reading level. In (Quarteroni and Manandhar, 2006), we introduce a hybrid QA-IR system based on a a user model. In this paper we focus on how the system filters and re-ranks the search engine results for a query according to their reading difficulty, providing user-tailored answers.

Incorporating user models in question answering to improve readability