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Analyzing dialog coherence using transition patterns in lexical and semantic features

Purandare, A and Litman, D (2008) Analyzing dialog coherence using transition patterns in lexical and semantic features. In: UNSPECIFIED.

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In this paper, we present methods to analyze dialog coherence that help us to automatically distinguish between coherent and incoherent conversations. We build a machine learning classifier using local transition patterns that span over adjacent dialog turns and encode lexical as well as semantic information in dialogs. We evaluate our algorithm on the Switchboard dialog corpus by treating original Switchboard dialogs as our coherent (positive) examples. Incoherent (negative) examples are created by randomly shuffling turns from these Switchboard dialogs. Results are very promising with the accuracy of 89% (over 50% baseline) when incoherent dialogs show both random order as well as random content (topics), and 68% when incoherent dialogs are random ordered but on-topic. We also present experiments on a newspaper text corpus and compare our findings on the two datasets. Copyright © 2008, Association for the Advancement of Artificial Intelligence ( All rights reserved.


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Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
CreatorsEmailPitt UsernameORCID
Purandare, A
Litman, Ddlitman@pitt.eduDLITMAN
Centers: University Centers > Learning Research and Development Center (LRDC)
Date: 17 November 2008
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: Proceedings of the 21th International Florida Artificial Intelligence Research Society Conference, FLAIRS-21
Page Range: 195 - 200
Event Type: Conference
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Computer Science
Dietrich School of Arts and Sciences > Intelligent Systems
Refereed: Yes
ISBN: 9781577353652
Date Deposited: 21 Nov 2014 19:38
Last Modified: 02 Feb 2019 15:59


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