Modern Information Retrieval
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Finding similar questions in large question and answer archives
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Retrieval models for question and answer archives
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SS '10 Proceedings of the NAACL HLT 2010 Workshop on Semantic Search
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EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
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In this paper we address the problem of question recommendation from large archives of community question answering data by exploiting the users' information needs. Our experimental results indicate that questions based on the same or similar information need can provide excellent question recommendation. We show that translation model can be effectively utilized to predict the information need given only the user's query question. Experiments show that the proposed information need prediction approach can improve the performance of question recommendation.