research-article

Micropinion generation: an unsupervised approach to generating ultra-concise summaries of opinions

Authors:

Kavita Ganesan,

ChengXiang Zhai,

Evelyne ViegasAuthors Info & Claims

WWW '12: Proceedings of the 21st international conference on World Wide Web

Pages 869 - 878

https://doi.org/10.1145/2187836.2187954

Published: 16 April 2012 Publication History

Abstract

This paper presents a new unsupervised approach to generating ultra-concise summaries of opinions. We formulate the problem of generating such a micropinion summary as an optimization problem, where we seek a set of concise and non-redundant phrases that are readable and represent key opinions in text. We measure representativeness based on a modified mutual information function and model readability with an n-gram language model. We propose some heuristic algorithms to efficiently solve this optimization problem. Evaluation results show that our unsupervised approach outperforms other state of the art summarization methods and the generated summaries are informative and readable.

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Cited By

Cheng GLiu QQu Y(2022)Generating Characteristic Summaries for Entity DescriptionsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3144391(1-1)Online publication date: 2022
https://doi.org/10.1109/TKDE.2022.3144391
Das SNayak J(2022)Customer Segmentation via Data Mining Techniques: State-of-the-Art ReviewComputational Intelligence in Data Mining10.1007/978-981-16-9447-9_38(489-507)Online publication date: 7-May-2022
https://doi.org/10.1007/978-981-16-9447-9_38
Chen HDong CFan LLoukides GPissis SStougie L(2021)Differentially Private String Sanitization for Frequency-Based Mining Tasks2021 IEEE International Conference on Data Mining (ICDM)10.1109/ICDM51629.2021.00014(41-50)Online publication date: Dec-2021
https://doi.org/10.1109/ICDM51629.2021.00014
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Micropinion generation: an unsupervised approach to generating ultra-concise summaries of opinions
1. Computing methodologies
  1. Artificial intelligence

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Published In

cover image ACM Other conferences

WWW '12: Proceedings of the 21st international conference on World Wide Web

April 2012

1078 pages

ISBN:9781450312295

DOI:10.1145/2187836

General Chairs:
Alain Mille
Université de Lyon, France
,
Fabien Gandon
INRIA, France
,
Jacques Misselis
HP, France
,
Program Chairs:
Michael Rabinovich
Case Western Reserve University, USA
,
Steffen Staab
University of Koblenz-Landau, Germany

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Univ. de Lyon: Universite de Lyon

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

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WWW 2012

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Univ. de Lyon

WWW 2012: 21st World Wide Web Conference 2012

April 16 - 20, 2012

Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Cheng GLiu QQu Y(2022)Generating Characteristic Summaries for Entity DescriptionsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3144391(1-1)Online publication date: 2022
https://doi.org/10.1109/TKDE.2022.3144391
Das SNayak J(2022)Customer Segmentation via Data Mining Techniques: State-of-the-Art ReviewComputational Intelligence in Data Mining10.1007/978-981-16-9447-9_38(489-507)Online publication date: 7-May-2022
https://doi.org/10.1007/978-981-16-9447-9_38
Chen HDong CFan LLoukides GPissis SStougie L(2021)Differentially Private String Sanitization for Frequency-Based Mining Tasks2021 IEEE International Conference on Data Mining (ICDM)10.1109/ICDM51629.2021.00014(41-50)Online publication date: Dec-2021
https://doi.org/10.1109/ICDM51629.2021.00014
Aamir MJan AMukhtar NKhan MAli ZAbro WYurong G(2021)An Unsupervised Graph-Based Hybrid Approach for Opinion Summarization2021 18th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)10.1109/ICCWAMTIP53232.2021.9674086(83-88)Online publication date: 17-Dec-2021
https://doi.org/10.1109/ICCWAMTIP53232.2021.9674086
Canbolat ZPinarbasi F(2020)Augmented Reality and Mobile ConsumersManagerial Challenges and Social Impacts of Virtual and Augmented Reality10.4018/978-1-7998-2874-7.ch005(76-94)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-2874-7.ch005
Mirtalaie MHussain O(2020)Sentiment aggregation of targeted features by capturing their dependencies: Making sense from customer reviewsInternational Journal of Information Management10.1016/j.ijinfomgt.2020.10209753(102097)Online publication date: Aug-2020
https://doi.org/10.1016/j.ijinfomgt.2020.102097
Sheela JJanet B(2020)RETRACTED ARTICLE: An abstractive summary generation system for customer reviews and news article using deep learningJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-020-02412-112:7(7363-7373)Online publication date: 3-Aug-2020
https://doi.org/10.1007/s12652-020-02412-1
Krishna Rohit SShrivastava M(2019)Using Argumentative Semantic Feature for Summarization2019 IEEE 13th International Conference on Semantic Computing (ICSC)10.1109/ICOSC.2019.8665523(456-461)Online publication date: Jan-2019
https://doi.org/10.1109/ICOSC.2019.8665523
Loures TS. Vaz de Melo PVeloso A(2018)Is it possible to describe television series from online comments?Journal of Internet Services and Applications10.1186/s13174-018-0096-19:1Online publication date: 15-Dec-2018
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Jin JLiu YJi PKwong C(2018)Review on Recent Advances in Information Mining From Big Consumer Opinion Data for Product DesignJournal of Computing and Information Science in Engineering10.1115/1.404108719:1Online publication date: 17-Sep-2018
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