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Personalize Review Selection Using PeRView

  • Muhmmad Al-khiza’ay
  • Noora Alallaq
  • Qusay Alanoz
  • Adil Al-Azzawi
  • N. Maheswari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11061)

Abstract

In the contemporary era, online reviews have an impact on people of all walks of life while choosing appropriate reviews that satisfied user preferences. Personalized reviews selection that is highly relevant to high coverage concerning matching with micro-reviews is the main problem that is considered in this paper. Toward this end, select a personalized subset of reviews are suggested. However, none of the existing research has taken into consideration the personalization of reviews. We proposed a framework known as PeRView for personalized review selection using micro-reviews. The proposed approach shows that our framework can determine and select the best subset of personalized reviews. Based on metric evaluation approach which considered personalized matching score and subset size.

Keywords

Online reviews Micro-reviews Review selection Personalized review selection 

Notes

Acknowledgement

This work is supported by the practical training project of high-level talents cross-training of Beijing colleges and universities (BUCEA-2018).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Muhmmad Al-khiza’ay
    • 1
  • Noora Alallaq
    • 1
  • Qusay Alanoz
    • 2
  • Adil Al-Azzawi
    • 3
    • 4
  • N. Maheswari
    • 5
  1. 1.School of Information Technology, Faculty of Science, Engineering and Built EnvironmentDeakin UniversityGeelongAustralia
  2. 2.Faculty of Mathematics and Computer ScienceUniversity of LodzLodzPoland
  3. 3.Electrical Engineering and Computer Science DepartmentUniversity of Missouri-Columbia MissouriColumbiaUSA
  4. 4.College of Science, Computer Science DepartmentUniversity of DiyalaBaqubahIraq
  5. 5.School of Computing Science and EngineeringVellore Institute of TechnologyChennaiIndia

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