research-article

Rated aspect summarization of short comments

Authors:

ChengXiang Zhai,

Neel SundaresanAuthors Info & Claims

WWW '09: Proceedings of the 18th international conference on World wide web

Pages 131 - 140

https://doi.org/10.1145/1526709.1526728

Published: 20 April 2009 Publication History

Abstract

Web 2.0 technologies have enabled more and more people to freely comment on different kinds of entities (e.g. sellers, products, services). The large scale of information poses the need and challenge of automatic summarization. In many cases, each of the user-generated short comments comes with an overall rating. In this paper, we study the problem of generating a ``rated aspect summary'' of short comments, which is a decomposed view of the overall ratings for the major aspects so that a user could gain different perspectives towards the target entity. We formally define the problem and decompose the solution into three steps. We demonstrate the effectiveness of our methods by using eBay sellers' feedback comments. We also quantitatively evaluate each step of our methods and study how well human agree on such a summarization task. The proposed methods are quite general and can be used to generate rated aspect summary automatically given any collection of short comments each associated with an overall rating.

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Cited By

Adhikary PSrivastava AKumar SSingh SManuja PGopinath JKrishnan VGupta SDeb KChakraborty T(2024)Exploring the Efficacy of Large Language Models in Summarizing Mental Health Counseling Sessions: Benchmark StudyJMIR Mental Health10.2196/5730611(e57306)Online publication date: 23-Jul-2024
https://doi.org/10.2196/57306
Wang YZhou YWang MChen ZCai ZChen JLeung V(2024)Multidocument Aspect Classification for Aspect-Based Abstractive SummarizationIEEE Transactions on Computational Social Systems10.1109/TCSS.2023.325272311:1(1483-1492)Online publication date: Feb-2024
https://doi.org/10.1109/TCSS.2023.3252723
Hayatin NAlias SHung L(2024)Trends and challenges in sentiment summarization: a systematic review of aspect extraction techniquesKnowledge and Information Systems10.1007/s10115-024-02075-w66:7(3671-3717)Online publication date: 9-May-2024
https://doi.org/10.1007/s10115-024-02075-w
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Index Terms

Rated aspect summarization of short comments
1. Information systems
  1. Information retrieval

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Published In

cover image ACM Conferences

WWW '09: Proceedings of the 18th international conference on World wide web

April 2009

1280 pages

ISBN:9781605584874

DOI:10.1145/1526709

General Chairs:
Juan Quemada
DIT-UPM
,
Gonzalo León
DIT-UPM
,
Program Chairs:
Yoelle Maarek
Google Inc., Israel
,
Wolfgang Nejdl
L3S and Hannover University

Copyright © 2009 IW3C2 org.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 April 2009

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WWW '09

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WWW '09: The 18th International World Wide Web Conference

April 20 - 24, 2009

Madrid, Spain

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

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Cited By

Adhikary PSrivastava AKumar SSingh SManuja PGopinath JKrishnan VGupta SDeb KChakraborty T(2024)Exploring the Efficacy of Large Language Models in Summarizing Mental Health Counseling Sessions: Benchmark StudyJMIR Mental Health10.2196/5730611(e57306)Online publication date: 23-Jul-2024
https://doi.org/10.2196/57306
Wang YZhou YWang MChen ZCai ZChen JLeung V(2024)Multidocument Aspect Classification for Aspect-Based Abstractive SummarizationIEEE Transactions on Computational Social Systems10.1109/TCSS.2023.325272311:1(1483-1492)Online publication date: Feb-2024
https://doi.org/10.1109/TCSS.2023.3252723
Hayatin NAlias SHung L(2024)Trends and challenges in sentiment summarization: a systematic review of aspect extraction techniquesKnowledge and Information Systems10.1007/s10115-024-02075-w66:7(3671-3717)Online publication date: 9-May-2024
https://doi.org/10.1007/s10115-024-02075-w
Ahmad SLaroche M(2023)Extracting marketing information from product reviews: a comparative study of latent semantic analysis and probabilistic latent semantic analysisJournal of Marketing Analytics10.1057/s41270-023-00218-611:4(662-676)Online publication date: 8-Apr-2023
https://doi.org/10.1057/s41270-023-00218-6
Kumar SGhosal TEkbal A(2023)DeepMetaGen: an unsupervised deep neural approach to generate template-based meta-reviews leveraging on aspect category and sentiment analysis from peer reviewsInternational Journal on Digital Libraries10.1007/s00799-023-00348-324:4(263-281)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1007/s00799-023-00348-3
Nguyen MTran DPhan VNguyen L(2023)Towards Social Context Summarization with Convolutional Neural NetworksComputational Linguistics and Intelligent Text Processing10.1007/978-3-031-23804-8_27(341-353)Online publication date: 26-Feb-2023
https://doi.org/10.1007/978-3-031-23804-8_27
Peng QYou LFeng HDu WZheng KZhu FXu X(2022)Jointly Modeling Aspect Information and Ratings for Review Rating PredictionElectronics10.3390/electronics1121353211:21(3532)Online publication date: 29-Oct-2022
https://doi.org/10.3390/electronics11213532
Zhao MYang YLi MWang JWu WRen Pde Rijke MRen ZAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)Personalized Abstractive Opinion TaggingProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3532037(1066-1076)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3477495.3532037
Liang TWang WLv F(2022)Weakly Supervised Domain Adaptation for Aspect Extraction via Multilevel Interaction TransferIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2021.307147433:10(5818-5829)Online publication date: Oct-2022
https://doi.org/10.1109/TNNLS.2021.3071474
Alshehri JStanojevic MDragut EObradovic Z(2022)On Label Quality in Class Imbalance Setting -A Case Study2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)10.1109/ICMLA55696.2022.00256(1666-1671)Online publication date: Dec-2022
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