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9

EMNLP
2010

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Learning the Relative Usefulness of Questions in Community QA

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Learning the Relative Usefulness of Questions in Community QA

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We present a machine learning approach for the task of ranking previously answered questions in a question repository with respect to their relevance to a new, unanswered reference question. The ranking model is trained on a collection of question groups manually annotated with a partial order relation reflecting the relative utility of questions inside each group. Based on a set of meaning and structure aware features, the new ranking model is able to substantially outperform more straightforward, unsupervised similarity measures.

Razvan C. Bunescu, Yunfeng Huang

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EMNLP 2010 | Natural Language Processing | Ranking Model | Unanswered Reference Question | Unsupervised Similarity Measures |

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Added	11 Feb 2011
Updated	11 Feb 2011
Type	Journal
Year	2010
Where	EMNLP
Authors	Razvan C. Bunescu, Yunfeng Huang

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