Projects per year
Online forum discussions proceed differently from face-to-face conversations and any single thread on an online forum contains posts on different subtopics. This work aims to characterize the content of a forum thread as a conversation tree of topics. We present models that jointly per- form two tasks: segment a thread into sub-parts, and assign a topic to each part. Our core idea is a definition of topic structure using probabilistic grammars. By leveraging the flexibility of two grammar formalisms, Context-Free Grammars and Linear Context-Free Rewriting Systems, our models create desirable structures for forum threads: our topic segmentation is hierarchical, links non-adjacent segments on the same topic, and jointly labels the topic during segmentation. We show that our models outperform a number of tree generation baselines.
|Title of host publication||Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing|
|Place of Publication||Lisbon, Portugal|
|Publisher||Association for Computational Linguistics|
|Number of pages||11|
|Publication status||Published - 1 Sep 2015|