Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
The TRAINS 93 Dialogues
Dialogue act modeling for automatic tagging and recognition of conversational speech
Computational Linguistics
Applied morphological processing of English
Natural Language Engineering
Dialogue act tagging with Transformation-Based Learning
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
MATCH: an architecture for multimodal dialogue systems
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Combining lexical, syntactic and prosodic cues for improved online dialog act tagging
Computer Speech and Language
ITSPOKE: an intelligent tutoring spoken dialogue system
HLT-NAACL--Demonstrations '04 Demonstration Papers at HLT-NAACL 2004
Tagging and linking web forum posts
CoNLL '10 Proceedings of the Fourteenth Conference on Computational Natural Language Learning
Exploiting conversational features to detect high-quality blog comments
Canadian AI'11 Proceedings of the 24th Canadian conference on Advances in artificial intelligence
Predicting thread discourse structure over technical web forums
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Unsupervised modeling of dialog acts in asynchronous conversations
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Hierarchical conversation structure prediction in multi-party chat
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Combining verbal and nonverbal features to overcome the 'information gap' in task-oriented dialogue
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
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We explore the task of automatically classifying dialogue acts in 1-on-1 online chat forums, an increasingly popular means of providing customer service. In particular, we investigate the effectiveness of various features and machine learners for this task. While a simple bag-of-words approach provides a solid baseline, we find that adding information from dialogue structure and inter-utterance dependency provides some increase in performance; learners that account for sequential dependencies (CRFs) show the best performance. We report our results from testing using a corpus of chat dialogues derived from online shopping customer-feedback data.