Utilizing Review Summarization in a Spoken Recommendation System

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 summ...

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Main Authors: Liu, Jingjing, Seneff, Stephanie, Zue, Victor
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: Association for Computational Linguistics 2011
Online Access:http://hdl.handle.net/1721.1/62198
https://orcid.org/0000-0003-2602-0862
https://orcid.org/0000-0001-8191-1049
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author Liu, Jingjing
Seneff, Stephanie
Zue, Victor
author2 Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
author_facet Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Liu, Jingjing
Seneff, Stephanie
Zue, Victor
author_sort Liu, Jingjing
collection MIT
description 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.
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spelling mit-1721.1/621982022-09-26T15:09:42Z Utilizing Review Summarization in a Spoken Recommendation System Liu, Jingjing Seneff, Stephanie Zue, Victor Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Zue, Victor Liu, Jingjing Seneff, Stephanie Zue, Victor 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. T-Party Project Quanta Computer (Firm) 2011-04-13T19:33:15Z 2011-04-13T19:33:15Z 2010-09 Article http://purl.org/eprint/type/ConferencePaper http://hdl.handle.net/1721.1/62198 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 https://orcid.org/0000-0003-2602-0862 https://orcid.org/0000-0001-8191-1049 en_US http://www.sigdial.org/workshops/workshop11/proc/pdf/SIGDIAL16.pdf Proceedings of SIGDIAL, Special Interest Group on Discourse and Dialogue, 11th Annual Meeting Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Association for Computational Linguistics MIT web domain
spellingShingle Liu, Jingjing
Seneff, Stephanie
Zue, Victor
Utilizing Review Summarization in a Spoken Recommendation System
title Utilizing Review Summarization in a Spoken Recommendation System
title_full Utilizing Review Summarization in a Spoken Recommendation System
title_fullStr Utilizing Review Summarization in a Spoken Recommendation System
title_full_unstemmed Utilizing Review Summarization in a Spoken Recommendation System
title_short Utilizing Review Summarization in a Spoken Recommendation System
title_sort utilizing review summarization in a spoken recommendation system
url http://hdl.handle.net/1721.1/62198
https://orcid.org/0000-0003-2602-0862
https://orcid.org/0000-0001-8191-1049
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