222-229.
the target. The second (denoted as P (¯ a| q)) is used ¯
D. Bernhard and I. Gurevych. 2009. Combining lexicalto denote the translation probability with the answer
semantic resources with question & answer archivesfor translation-based answer finding. InProceedingsas the source and the question as the target. Table 7
of ACL, pages 728-736.provides the comparison. From this Table, we see
P. F. Brown and V. J. D. Pietra and S. A. D. Pietra andthat the pooling strategy significantly outperforms
R. L. Mercer. 1993. The mathematics of statisticalthe two baseline methods for question retrieval (row
machine translation: parameter estimation. Computa-13 and row 14 vs. row 15).
tional Linguistics, 19(2):263-311.R. Bunescu and Y. Huang. 2010. Learning the relativeusefulness of questions in community QA. In Pro-5 Conclusions and Future Work
ceedings of EMNLP, pages 97-107.X. Cao and G. Cong and B. Cui and C. S. Jensen. 2010.In this paper, we propose a novel phrase-based trans-
A generalized framework of exploring category infor-lation model for question retrieval. Compared to
mation for question retrieval in community questionthe traditional word-based translation models, the
answer archives. InProceedings of WWW.proposed approach is more effective in that it can
D. Chiang. 2005. A hierarchical phrase-based model forcapture contextual information instead of translating
statistical machine translation. InProceedings of ACL.single words in isolation. Experiments conducted
H. Duan and Y. Cao and C. Y. Lin and Y. Yu. 2008.Searching questions by identifying questions topicson real Q&A data demonstrate that the phrase-
and question focus. In Proceedings of ACL, pagesbased translation model significantly outperforms
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