research-article

Effective Selection of a Compact and High-Quality Review Set with Information Preservation

Authors:

Yinghui (Catherine) Yang,

Jun HeAuthors Info & Claims

ACM Transactions on Management Information Systems (TMIS), Volume 10, Issue 4

Article No.: 15, Pages 1 - 22

https://doi.org/10.1145/3369395

Published: 10 December 2019 Publication History

Abstract

Consumers increasingly make informed buying decisions based on reading online reviews for products and services. Due to the large volume of available online reviews, consumers hardly have the time and patience to read them all. This article aims to select a compact set of high-quality reviews that can cover a specific set of product features and related consumer sentiments. Selecting such a subset of reviews can significantly save the time spent on reading reviews while preserving the information needed. A unique review selection problem is defined and modeled as a bi-objective combinatorial optimization problem, which is then transformed into a minimum-cost set cover problem that is NP-complete. Several approximation algorithms are then designed, which can sustain performance guarantees in polynomial time. Our effective selection algorithms can also be upgraded to handle dynamic situations. Comprehensive experiments conducted on twelve real datasets demonstrate that the proposed algorithms significantly outperform benchmark methods by generating a more compact review set with much lower computational cost. The number of reviews selected is much smaller compared to the quantity of all available reviews, and the selection efficiency is deeply increased by accelerating strategies, making it very practical to adopt the methods in real-world online applications.

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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: 30-Mar-2023
https://dl.acm.org/doi/10.1145/3587265
Guo YGuo SJin ZKaul SGotz DCao N(2022)Survey on Visual Analysis of Event Sequence DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.310041328:12(5091-5112)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1109/TVCG.2021.3100413
Cai YKe WCui EYu F(2022)A deep recommendation model of cross-grained sentiments of user reviews and ratingsInformation Processing and Management: an International Journal10.1016/j.ipm.2021.10284259:2Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.ipm.2021.102842
Show More Cited By

Index Terms

Effective Selection of a Compact and High-Quality Review Set with Information Preservation
1. Applied computing
  1. Operations research
    1. Decision analysis
      1. Multi-criterion optimization and decision-making
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals

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Published In

cover image ACM Transactions on Management Information Systems

ACM Transactions on Management Information Systems Volume 10, Issue 4

December 2019

98 pages

ISSN:2158-656X

EISSN:2158-6578

DOI:10.1145/3374918

Editor:
Daniel Zeng
Chinese Academy of Sciences, China

Issue’s Table of Contents

Copyright © 2019 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 December 2019

Accepted: 01 October 2019

Revised: 01 August 2019

Received: 01 December 2018

Published in TMIS Volume 10, Issue 4

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The MOE Project of Key Research Institute of Humanities and Social Sciences at Universities
National Natural Science Foundation of China

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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: 30-Mar-2023
https://dl.acm.org/doi/10.1145/3587265
Guo YGuo SJin ZKaul SGotz DCao N(2022)Survey on Visual Analysis of Event Sequence DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.310041328:12(5091-5112)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1109/TVCG.2021.3100413
Cai YKe WCui EYu F(2022)A deep recommendation model of cross-grained sentiments of user reviews and ratingsInformation Processing and Management: an International Journal10.1016/j.ipm.2021.10284259:2Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.ipm.2021.102842
Chen GXiao SZhang CWang W(2022)An orthogonal-space-learning-based method for selecting semantically helpful reviewsElectronic Commerce Research and Applications10.1016/j.elerap.2022.10115453(101154)Online publication date: May-2022
https://doi.org/10.1016/j.elerap.2022.101154
Liu YWu A(2021)POI Recommendation Method Using Deep Learning in Location-Based Social NetworksWireless Communications & Mobile Computing10.1155/2021/91208642021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/9120864

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