Utilizing Review Summarization in a Spoken Recommendation System
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Zue_Utilizing review.pdf
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Author(s)
Liu, Jingjing
Seneff, Stephanie
Zue, Victor
Date Issued
September 2010
Journal
Proceedings of SIGDIAL, Special Interest Group on Discourse and Dialogue, 11th Annual Meeting
Publisher
Association for Computational Linguistics
Citation
Liu, Jingjing, Stephanie Seneff, Victor Zue. "Utilizing review summarization in a spoken recommendation system." Proceedings of SIGDIAL, 2010: the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp. 83-86. Copyright 2010 Association for Computational Linguistics
Version
Author's final manuscript
Abstract
In this paper we present a framework for spoken recommendation
systems. To provide reliable recommendations
to users, we incorporate a review summarization
technique which extracts informative opinion
summaries from grass-roots users‘ reviews. The dialogue
system then utilizes these review summaries to
support both quality-based opinion inquiry and feature-
specific entity search. We propose a probabilistic
language generation approach to automatically creating
recommendations in spoken natural language
from the text-based opinion summaries. A user study
in the restaurant domain shows that the proposed approaches
can effectively generate reliable and helpful
recommendations in human-computer conversations.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
http://www.sigdial.org/workshops/workshop11/proc/pdf/SIGDIAL16.pdf
