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Exploring reviews and ratings on reviews for personalized search

  • Yang Yang
  • , Shuyue Hu
  • , Yi Cai*
  • , Qing Du
  • , Ho-Fung Leung
  • , Raymond Y. K. Lau
  • *Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

With the development of e-commerce, e-commerce websites become very popular. People write reviews on products and rate the helpfulness of reviews in these websites. Reviews written by a user and reviews rated by a user actually reflect a user’s interests and disinterest. Thus, they are very useful for user profiling. In this paper, we explore users’ reviews and ratings on reviews for personalized search and propose a review-based user profiling method. And we also propose a prioritybased result ranking strategy. For evaluation, we conduct experiments on a real-life data set. The experimental results show that our method can significantly improve the retrieval quality.
Original languageEnglish
Title of host publicationCurrent Developments in Web Based Learning
Subtitle of host publicationICWL 2015 International Workshops, KMEL, IWUM, LA, Revised Selected Papers
EditorsDi Zou, Zhiguo Gong, Dickson K.W. Chiu
PublisherSpringer Verlag
Pages140-150
Volume9584
ISBN (Print)9783319328645
DOIs
Publication statusPublished - 2016
EventInternational Conference on Web Based Learning, ICWL 2015 - Guangzhou, China
Duration: 5 Nov 20158 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9584
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Web Based Learning, ICWL 2015
PlaceChina
CityGuangzhou
Period5/11/158/11/15

Research Keywords

  • Personalized search
  • Review
  • User profiling

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