Paper: Classifying Dialogue Acts in One-on-One Live Chats

ACL ID D10-1084
Title Classifying Dialogue Acts in One-on-One Live Chats
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2010
Authors

We explore the task of automatically classify- ingdialogueactsin1-on-1onlinechatforums, an increasingly popular means of providing customer service. In particular, we investi- gate the effectiveness of various features and machine learners for this task. While a sim- ple bag-of-words approach provides a solid baseline, wefindthataddinginformationfrom dialogue structure and inter-utterance depen- dency provides some increase in performance; learners that account for sequential dependen- cies (CRFs) show the best performance. We report our results from testing using a corpus of chat dialogues derived from online shop- ping customer-feedback data.