Personalized landmark recommendation algorithm based on language-specific satisfaction prediction using heterogeneous open data sources

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

Abstract

This paper proposes a personalized landmark recommendation algorithm based on the prediction of users' satisfaction on landmarks. We have accumulated 270,239 user-generated comments from travel websites of Ctrip, Jaran and TripAdvisor for 196 landmarks in Tokyo, Japan. We find that users do have different satisfaction on landmarks depending on their commonly used languages and travel websites. Then we establish a database for landmarks with abundant and accurate landmark type and landmark satisfaction information. Finally, we propose an effective personalized landmark satisfaction prediction algorithm based on users' landmark type, language and travel website preferences. After that, landmarks with the top-6 highest satisfaction are provided to the user for a one-day visit plan in Tokyo. Experimental results demonstrate that the proposed algorithm can recommend landmarks that fit the user's preferences and our algorithm also successfully predicts the user's landmark satisfaction with a low error rate less than 7%, which is superior to other previous studies.

Original languageEnglish
Title of host publicationProceedings - 2018 10th International Conference on Computational Intelligence and Communication Networks, CICN 2018
EditorsD. M. Akbar Hussain, Geetam Singh Tomar, Geetam Singh Tomar
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages70-76
Number of pages7
ISBN (Electronic)9781538625774
DOIs
Publication statusPublished - 2018 Aug
Event10th International Conference on Computational Intelligence and Communication Networks, CICN 2018 - Esbjerg, Denmark
Duration: 2018 Aug 172018 Aug 19

Publication series

NameProceedings - 2018 10th International Conference on Computational Intelligence and Communication Networks, CICN 2018

Conference

Conference10th International Conference on Computational Intelligence and Communication Networks, CICN 2018
CountryDenmark
CityEsbjerg
Period18/8/1718/8/19

Keywords

  • Landmark satisfaction prediction
  • Personalized landmark recommendation
  • User-generated comment

ASJC Scopus subject areas

  • Control and Optimization
  • Computer Networks and Communications
  • Computer Science Applications
  • Artificial Intelligence

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  • Cite this

    Bao, S., Yanagisawa, M., & Togawa, N. (2018). Personalized landmark recommendation algorithm based on language-specific satisfaction prediction using heterogeneous open data sources. In D. M. Akbar Hussain, G. S. Tomar, & G. S. Tomar (Eds.), Proceedings - 2018 10th International Conference on Computational Intelligence and Communication Networks, CICN 2018 (pp. 70-76). [8864958] (Proceedings - 2018 10th International Conference on Computational Intelligence and Communication Networks, CICN 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CICN.2018.8864958