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

研究成果: Conference contribution

抜粋

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.

元の言語English
ホスト出版物のタイトルProceedings - 2018 10th International Conference on Computational Intelligence and Communication Networks, CICN 2018
編集者D. M. Akbar Hussain, Geetam Singh Tomar, Geetam Singh Tomar
出版者Institute of Electrical and Electronics Engineers Inc.
ページ70-76
ページ数7
ISBN(電子版)9781538625774
DOI
出版物ステータスPublished - 2018 8
イベント10th International Conference on Computational Intelligence and Communication Networks, CICN 2018 - Esbjerg, Denmark
継続期間: 2018 8 172018 8 19

出版物シリーズ

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

Conference

Conference10th International Conference on Computational Intelligence and Communication Networks, CICN 2018
Denmark
Esbjerg
期間18/8/1718/8/19

ASJC Scopus subject areas

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

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  • これを引用

    Bao, S., Yanagisawa, M., & Togawa, N. (2018). Personalized landmark recommendation algorithm based on language-specific satisfaction prediction using heterogeneous open data sources. : D. M. Akbar Hussain, G. S. Tomar, & G. S. Tomar (版), 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