Attention, intentions, and the structure of discourse
Computational Linguistics
A computational model of expectation-driven mixed-initiative dialog processing
A computational model of expectation-driven mixed-initiative dialog processing
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Advances in kernel methods
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Computational Linguistics
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Computational Linguistics
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ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
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ACL '88 Proceedings of the 26th annual meeting on Association for Computational Linguistics
The role of initiative in tutorial dialogue
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
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Natural Language Engineering
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Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
An interactive tool for supporting error analysis for text mining
HLT-DEMO '10 Proceedings of the NAACL HLT 2010 Demonstration Session
Importance-Driven Turn-Bidding for spoken dialogue systems
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Computational representation of discourse practices across populations in task-based dialogue
Proceedings of the 4th international conference on Intercultural Collaboration
Group composition and intelligent dialogue tutors for impacting students' academic self-efficacy
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
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Proceedings of the 17th ACM international conference on Supporting group work
Annotation of adversarial and collegial social actions in discourse
LAW VI '12 Proceedings of the Sixth Linguistic Annotation Workshop
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
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We present a novel computational formulation of speaker authority in discourse. This notion, which focuses on how speakers position themselves relative to each other in discourse, is first developed into a reliable coding scheme (0.71 agreement between human annotators). We also provide a computational model for automatically annotating text using this coding scheme, using supervised learning enhanced by constraints implemented with Integer Linear Programming. We show that this constrained model's analyses of speaker authority correlates very strongly with expert human judgments (r2 coefficient of 0.947).