Learning the Relative Usefulness of Questions in Community QA
نویسندگان
چکیده
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 outperformmore straightforward, unsupervised similarity measures.
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