Weighted Combination of Q&A Retrieval Models Based on Part-of-Speech of Question Word

Question and answer archives have become useful information resources with increase of community based question and answer service. For effective question and answering system, it is important to find semantically similar questions and retrieve its answer from the archive for user's question. In this paper, we propose a weighted combination of retrieval models for question and answer archives. In contrast to well-known translation based language model, the proposed model reflects significance of each word in user's question by giving variant weight to the word depending on its part-of-speech. In experiment, our model improves performance considerably when compared to conventional ones.