Paper: Learning the Relative Usefulness of Questions in Community QA

ACL ID D10-1010
Title Learning the Relative Usefulness of Questions in Community QA
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2010
Authors

We present a machine learning approach for the task of ranking previously answered ques- tions in a question repository with respect to their relevance to a new, unanswered refer- ence question. The ranking model is trained on a collection of question groups manually annotated with a partial order relation reflect- ing the relative utility of questions inside each group. Based on a set of meaning and struc- ture aware features, the new ranking model is abletosubstantiallyoutperformmorestraight- forward, unsupervised similarity measures.