Learning the Relative Usefulness of Questions in Community QA

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.

• Type: Journal
• Year: 2010
• Where: EMNLP
• Authors: Razvan C. Bunescu, Yunfeng Huang
• Keywords: EMNLP 2010, Natural Language Processing, Ranking Model, Unanswered Reference Question, Unsupervised Similarity Measures