Similarity-ranking method based on semantic computing for a context-aware system

Motoki Yokoyama, Yasushi Kiyoki, Tetsuya Mita

研究成果: Conference contribution

3 引用 (Scopus)

抜粋

Among the enormous variety of data in recent years, transportation data contain significant potential for understanding the information requirements and intention of passengers. In this paper, we propose a new information ranking method for passenger intention prediction and service recommendation. The method includes three main features, which include (1) predicting the intention of a used based on his/her current context, (2) selecting a subspace for service recommendation, and (3) ranking the services by the highest relevant order. By comparing the predicted results with a straightforward computation method, the experimental studies show the effectiveness and efficiency of the proposed method. The paper also describes the simplicity of our method over existing subspace selection methods.

元の言語English
ホスト出版物のタイトル2016 International Conference on Knowledge Creation and Intelligent Computing, KCIC 2016
出版者Institute of Electrical and Electronics Engineers Inc.
ページ21-27
ページ数7
ISBN(電子版)9781509052318
DOI
出版物ステータスPublished - 2017 3 20
イベント5th International Conference on Knowledge Creation and Intelligent Computing, KCIC 2016 - Manado, Indonesia
継続期間: 2016 11 152016 11 17

Other

Other5th International Conference on Knowledge Creation and Intelligent Computing, KCIC 2016
Indonesia
Manado
期間16/11/1516/11/17

    フィンガープリント

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence

これを引用

Yokoyama, M., Kiyoki, Y., & Mita, T. (2017). Similarity-ranking method based on semantic computing for a context-aware system. : 2016 International Conference on Knowledge Creation and Intelligent Computing, KCIC 2016 (pp. 21-27). [7883620] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/KCIC.2016.7883620