Abstract
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.
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CITATION STYLE
Quarteroni, S., & Manandhar, S. (2006). Incorporating User Models in Question Answering to Improve Readability. In EACL 2006 - 11th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Workshop on KRAQ 2006: Knowledge and Reasoning for Language Processing (pp. 50–57). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1641493.1641502
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