Tagging and Linking Web Forum Posts
Su Nam Kim, Li Wang, Timothy J. Baldwin · Conference on Computational Natural Language Learning · 2010
We propose a method for annotating post-to-post discourse structure in online user forum data, in the hopes of improving troubleshooting-oriented information access. We introduce the tasks of: (1) post classification, based on a novel dialogue act tag set; and (2) link classification. We also introduce three feature sets (structural features, post context features and semantic features) and experiment with three discriminative learners (maximum entropy, SVM-HMM and CRF). We achieve above-baseline results for both dialogue act and link classification, with interesting divergences in which feature sets perform well over the two sub-tasks, and go on to perform preliminary investigation of the interaction between post tagging and linking.