NDLI: An analysis of automatic content selection algorithms for spoken dialogue system summaries (2006)

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An analysis of automatic content selection algorithms for spoken dialogue system summaries (2006)

Content Provider	CiteSeerX
Author	Polifroni, Joseph Walker, Marilyn
Description	Previous work on information presentation in dialogue systems has argued that a user model is essential for selecting utterance content. Other work claims that the ability to browse the data is critical for supporting information-seeking behaviors in information retrieval applications, but does not specify how to provide browsing support. In this work, we test the hypothesis that automatically constructed summaries based on the current dialogue state and provided incrementally during the dialogue can support users ’ browsing activities. We examine the impact of three factors on summary efficacy: (1) the number and type of attributes selected for summary construction; (2) the use of a decision theoretic user model; and (3) the use of association rules derived automatically from the database subset currently in-focus. Our experimental results show that equally effective summaries can be constructed using either a combination of a user model with association rules, or the “Refiner ” method described in previous work. Index Terms — natural language interfaces, user modeling 1.
File Format	PDF
Language	English
Publisher Date	2006-01-01
Publisher Institution	In Proc. of the IEEE/ACL Conference on Spoken Language Technology
Access Restriction	Open
Subject Keyword	Summary Construction Previous Work Dialogue System Effective Summary Information Retrieval Application Dialogue System Summary Association Rule Refiner Method Work Claim Decision Theoretic User Model Current Dialogue State Index Term Natural Language Interface Summary Efficacy Information-seeking Behavior Experimental Result Automatic Content Selection Algorithm User Model Information Presentation Utterance Content
Content Type	Text
Resource Type	Article

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