Paper: Unsupervised Solution Post Identification from Discussion Forums

ACL ID P14-1015
Title Unsupervised Solution Post Identification from Discussion Forums
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014

Discussion forums have evolved into a de- pendable source of knowledge to solve common problems. However, only a mi- nority of the posts in discussion forums are solution posts. Identifying solution posts from discussion forums, hence, is an important research problem. In this pa- per, we present a technique for unsuper- vised solution post identification leverag- ing a so far unexplored textual feature, that of lexical correlations between problems and solutions. We use translation mod- els and language models to exploit lex- ical correlations and solution post char- acter respectively. Our technique is de- signed to not rely much on structural fea- tures such as post metadata since such features are often not uniformly available across forums. Our clustering-based itera- tive solution id...