Article

Utility scoring of product reviews

Authors:

Balaji VaradarajanAuthors Info & Claims

CIKM '06: Proceedings of the 15th ACM international conference on Information and knowledge management

Pages 51 - 57

https://doi.org/10.1145/1183614.1183626

Published: 06 November 2006 Publication History

Abstract

We identify a new task in the ongoing research in text sentiment analysis: predicting utility of product reviews, which is orthogonal to polarity classification and opinion extraction. We build regression models by incorporating a diverse set of features, and achieve highly competitive performance for utility scoring on three real-world data sets.

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Cited By

Sharma SSingh LTiwari R(2024)Design of an Efficient Integrated Feature Engineering based Deep Learning Model Using CNN for Customer’s Review Helpfulness PredictionWireless Personal Communications10.1007/s11277-023-10834-1133:4(2125-2161)Online publication date: 21-Feb-2024
https://doi.org/10.1007/s11277-023-10834-1
Pajola LChen DConti MSubrahmanian V(2023)A Novel Review Helpfulness Measure Based on the User-Review-Item ParadigmACM Transactions on the Web10.1145/358528017:4(1-31)Online publication date: 11-Jul-2023
https://dl.acm.org/doi/10.1145/3585280
Darvishi AKhosravi HRahimi ASadiq SGašević D(2023)Assessing the Quality of Student-Generated Content at Scale: A Comparative Analysis of Peer-Review ModelsIEEE Transactions on Learning Technologies10.1109/TLT.2022.322902216:1(106-120)Online publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1109/TLT.2022.3229022
Show More Cited By

Index Terms

Utility scoring of product reviews
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
  2. Machine learning
    1. Machine learning approaches
      1. Logical and relational learning
        Inductive logic learning
2. Information systems
  1. Information retrieval
  2. Information storage systems

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Published In

cover image ACM Conferences

CIKM '06: Proceedings of the 15th ACM international conference on Information and knowledge management

November 2006

916 pages

ISBN:1595934332

DOI:10.1145/1183614

General Chair:
Philip S. Yu
IBM T.J. Watson Research Center (USA)
,
Program Chairs:
Vassilis Tsotras
University of California-Riverside (USA)
,
Edward Fox
Virginia Tech (USA)
,
Bing Liu
University of Illinois at Chicago (USA)

Copyright © 2006 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: 06 November 2006

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CIKM06: Conference on Information and Knowledge Management

November 6 - 11, 2006

Virginia, Arlington, USA

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Citations

Cited By

Sharma SSingh LTiwari R(2024)Design of an Efficient Integrated Feature Engineering based Deep Learning Model Using CNN for Customer’s Review Helpfulness PredictionWireless Personal Communications10.1007/s11277-023-10834-1133:4(2125-2161)Online publication date: 21-Feb-2024
https://doi.org/10.1007/s11277-023-10834-1
Pajola LChen DConti MSubrahmanian V(2023)A Novel Review Helpfulness Measure Based on the User-Review-Item ParadigmACM Transactions on the Web10.1145/358528017:4(1-31)Online publication date: 11-Jul-2023
https://dl.acm.org/doi/10.1145/3585280
Darvishi AKhosravi HRahimi ASadiq SGašević D(2023)Assessing the Quality of Student-Generated Content at Scale: A Comparative Analysis of Peer-Review ModelsIEEE Transactions on Learning Technologies10.1109/TLT.2022.322902216:1(106-120)Online publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1109/TLT.2022.3229022
Ren GDiao LKim J(2023)DMFNExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.120344228:COnline publication date: 15-Oct-2023
https://dl.acm.org/doi/10.1016/j.eswa.2023.120344
Ünver M(2023)An Automatic Rating System Based on Review Sentiments and Intuitionistic Fuzzy SetsIntelligent and Fuzzy Systems10.1007/978-3-031-39774-5_22(177-184)Online publication date: 17-Aug-2023
https://doi.org/10.1007/978-3-031-39774-5_22
Miao QHu CXu F(2023)Using Reviewer Information to Improve Performance of Low-Quality Review DetectionComputational Linguistics and Intelligent Text Processing10.1007/978-3-031-23804-8_30(381-399)Online publication date: 26-Feb-2023
https://doi.org/10.1007/978-3-031-23804-8_30
Luo HSong WZhou W(2022)TipScreener: A Framework for Mining Tips for Online Review ReadersJournal of Theoretical and Applied Electronic Commerce Research10.3390/jtaer1704008717:4(1716-1740)Online publication date: 5-Dec-2022
https://doi.org/10.3390/jtaer17040087
Gupta AGirerd CDunna MZhang QSubbaraman RMorimoto TBharadia D(2022)Expanding the Horizons of Wireless SensingGetMobile: Mobile Computing and Communications10.1145/3511285.351129625:3(38-42)Online publication date: 11-Jan-2022
https://dl.acm.org/doi/10.1145/3511285.3511296
Salemi Parizi FWhitmire EPatel S(2022)AuraRingGetMobile: Mobile Computing and Communications10.1145/3511285.351129525:3(34-37)Online publication date: 11-Jan-2022
https://dl.acm.org/doi/10.1145/3511285.3511295
Zhang TMao S(2022)An Introduction to the Federated Learning StandardGetMobile: Mobile Computing and Communications10.1145/3511285.351129125:3(18-22)Online publication date: 11-Jan-2022
https://dl.acm.org/doi/10.1145/3511285.3511291
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