Serendipitous Page Recommendation on Web IndeX System with Potential Preferences

Xingyu Chen, Jun Nemoto, Motomichi Toyama

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

Abstract

Most recommendation systems excessively pursue the recommendation accuracy and give rise to over-specialization. However, the existing recommendation systems research has not studied serendipity much. Hence, the serendipitous item recommendation has received more attention in recent years. The serendipitous recommendation of our research is not included in the area that the user predict easily but recommends the keywords that match the potential preferences. Potential preferences are those that are present in the user profile, which the user may not know. In this research, we recommend keywords that can express serendipity by intersecting the relation between keywords mainly. Furthermore, we propose the related page recommendation method on Web IndeX System for recommending linked pages related to these serendipitous keywords based on the user's potential preferences.

Original languageEnglish
Title of host publication22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020 - Proceedings
EditorsMaria Indrawan-Santiago, Eric Pardede, Ivan Luiz Salvadori, Matthias Steinbauer, Ismail Khalil, Gabriele Kotsis
PublisherAssociation for Computing Machinery
Pages104-110
Number of pages7
ISBN (Electronic)9781450389228
DOIs
Publication statusPublished - 2020 Nov 30
Event22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020 - Virtual, Online, Thailand
Duration: 2020 Nov 302020 Dec 2

Publication series

NameACM International Conference Proceeding Series

Conference

Conference22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020
CountryThailand
CityVirtual, Online
Period20/11/3020/12/2

Keywords

  • Recommendation
  • Serendipity
  • Web IndeX System
  • Webpage

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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