A Reinforced Semi-supervised Neural Network for Helpful Review Identification

Yue Feng, Miao Fan, Mingming Sun, Ping Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

It is crucial to recommend helpful product reviews to consumers in e-commercial service, as the helpful ones can promote consumption. Existing methods for identifying helpful reviews are based on the supervised learning paradigm. The capacity of supervised methods, however, is limited by the lack of annotated reviews. In addition, there is a serious distributional bias between the labeled and unlabeled reviews. Therefore, this paper proposes a reinforced semi-supervised neural learning method (abbreviated as RSSNL) for helpful review identification, which can automatically select high-related unlabeled reviews to help training. Concretely, RSSNL composes with a reinforced unlabeled review selection policy and a semi-supervised pseudo-labeling review classifier. These two parts train jointly and integrate together based on the policy gradient framework. Extensive experiments on Amazon product reviews verify the effectiveness of RSSNL for using unlabeled reviews.

Original languageEnglish (US)
Title of host publicationCIKM 2020 - Proceedings of the 29th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages2021-2024
Number of pages4
ISBN (Electronic)9781450368599
DOIs
StatePublished - Oct 19 2020
Externally publishedYes
Event29th ACM International Conference on Information and Knowledge Management, CIKM 2020 - Virtual, Online, Ireland
Duration: Oct 19 2020Oct 23 2020

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference29th ACM International Conference on Information and Knowledge Management, CIKM 2020
Country/TerritoryIreland
CityVirtual, Online
Period10/19/2010/23/20

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

Keywords

  • natural language processing
  • reinforcement learning
  • semi-supervised learning

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