research-article

Selecting a comprehensive set of reviews

Authors:

Panayiotis Tsaparas,

Alexandros Ntoulas,

Evimaria TerziAuthors Info & Claims

KDD '11: Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 168 - 176

https://doi.org/10.1145/2020408.2020440

Published: 21 August 2011 Publication History

Abstract

Online user reviews play a central role in the decision-making process of users for a variety of tasks, ranging from entertainment and shopping to medical services. As user-generated reviews proliferate, it becomes critical to have a mechanism for helping the users (information consumers) deal with the information overload, and presenting them with a small comprehensive set of reviews that satisfies their information need. This is particularly important for mobile phone users, who need to make decisions quickly, and have a device with limited screen real-estate for displaying the reviews. Previous approaches have addressed the problem by ranking reviews according to their (estimated) helpfulness. However, such approaches do not account for the fact that the top few high-quality reviews may be highly redundant, repeating the same information, or presenting the same positive (or negative) perspective. In this work, we focus on the problem of selecting a comprehensive set of few high-quality reviews that cover many different aspects of the reviewed item. We formulate the problem as a maximum coverage problem, and we present a generic formalism that can model the different variants of review-set selection. We describe algorithms for the different variants we consider, and, whenever possible, we provide approximation guarantees with respect to the optimal solution. We also perform an experimental evaluation on real data in order to understand the value of coverage for users.

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Cited By

Zhang JLi XWang L(2023)A Review Selection Method Based on Consumer Decision Phases in E-commerceACM Transactions on Information Systems10.1145/358726542:1(1-27)Online publication date: 21-Aug-2023
https://dl.acm.org/doi/10.1145/3587265
Farhadi MGupta SSun STetali PWigal M(2023)Hardness and approximation of submodular minimum linear ordering problemsMathematical Programming10.1007/s10107-023-02038-z208:1-2(277-318)Online publication date: 14-Dec-2023
https://doi.org/10.1007/s10107-023-02038-z
Ordozgoiti BMahadevan AMatakos AGionis A(2022)Provable randomized rounding for minimum-similarity diversificationData Mining and Knowledge Discovery10.1007/s10618-021-00811-236:2(709-738)Online publication date: 4-Jan-2022
https://doi.org/10.1007/s10618-021-00811-2
Show More Cited By

Index Terms

Selecting a comprehensive set of reviews
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking
    2. Retrieval tasks and goals
  2. Information systems applications
    1. Data mining

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Published In

cover image ACM Conferences

KDD '11: Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining

August 2011

1446 pages

ISBN:9781450308137

DOI:10.1145/2020408

General Chair:
Chid Apte
IBM Research
,
Program Chairs:
Joydeep Ghosh
UT Austin
,
Padhraic Smyth
UC Irvine

Copyright © 2011 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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Publication History

Published: 21 August 2011

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KDD '11

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KDD '11: The 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 21 - 24, 2011

California, San Diego, USA

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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

Zhang JLi XWang L(2023)A Review Selection Method Based on Consumer Decision Phases in E-commerceACM Transactions on Information Systems10.1145/358726542:1(1-27)Online publication date: 21-Aug-2023
https://dl.acm.org/doi/10.1145/3587265
Farhadi MGupta SSun STetali PWigal M(2023)Hardness and approximation of submodular minimum linear ordering problemsMathematical Programming10.1007/s10107-023-02038-z208:1-2(277-318)Online publication date: 14-Dec-2023
https://doi.org/10.1007/s10107-023-02038-z
Ordozgoiti BMahadevan AMatakos AGionis A(2022)Provable randomized rounding for minimum-similarity diversificationData Mining and Knowledge Discovery10.1007/s10618-021-00811-236:2(709-738)Online publication date: 4-Jan-2022
https://doi.org/10.1007/s10618-021-00811-2
Bansal NBatra JFarhadi MTetali PMarx D(2021)Improved approximations for min sum vertex cover and generalized min sum set coverProceedings of the Thirty-Second Annual ACM-SIAM Symposium on Discrete Algorithms10.5555/3458064.3458126(986-1005)Online publication date: 10-Jan-2021
https://dl.acm.org/doi/10.5555/3458064.3458126
Shamim AQureshi MJabeen FLiaqat MBilal MJembre YAttique M(2021)Multi-Attribute Online Decision-Making Driven by Opinion MiningMathematics10.3390/math90808339:8(833)Online publication date: 11-Apr-2021
https://doi.org/10.3390/math9080833
Zhang JWang CChen G(2021)A Review Selection Method for Finding an Informative Subset from Online ReviewsINFORMS Journal on Computing10.1287/ijoc.2019.095033:1(280-299)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1287/ijoc.2019.0950
Jiang WChen JDing XWu JHe JWang G(2021)Review Summary Generation in Online Systems: Frameworks for Supervised and Unsupervised ScenariosACM Transactions on the Web10.1145/344801515:3(1-33)Online publication date: 13-May-2021
https://dl.acm.org/doi/10.1145/3448015
Bao ZLi WYin PChau M(2021)Examining the impact of review tag function on product evaluation and information perception of popular productsInformation Systems and e-Business Management10.1007/s10257-021-00532-5Online publication date: 27-May-2021
https://doi.org/10.1007/s10257-021-00532-5
Bonesso DBecker KPortet FLabbé C(2020)Ranking Hotel Reviews Based on User's Aspects Importance and OpinionsProceedings of the 4th International Conference on Natural Language Processing and Information Retrieval10.1145/3443279.3443280(157-162)Online publication date: 18-Dec-2020
https://dl.acm.org/doi/10.1145/3443279.3443280
Pimenta FLopes LGonçalves FCampos P(2020)Designing Positive Behavior Change Experiences: a Systematic Review and Sentiment Analysis based on Online User Reviews of Fitness and Nutrition Mobile ApplicationsProceedings of the 19th International Conference on Mobile and Ubiquitous Multimedia10.1145/3428361.3428403(152-161)Online publication date: 22-Nov-2020
https://dl.acm.org/doi/10.1145/3428361.3428403
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