A correlation computing method for integrating passengers and services in semantic anticipation

Motoki Yokoyama, Yasushi Kiyoki, Tetsuya Mita

研究成果: Conference contribution

抜粋

New information-provision focusing on individual passengers is expected in a railway environment. Our method realizes multiple semantic spaces, which are selected according to passenger's contexts. By using correlation metrics for the causal interaction of different semantic spaces, this method anticipates the passenger's needs and generates a ranking of services and facilities. Experimental study confirms that the ranking of passenger requirements for services and facilities would change appropriately in response to the causal interaction of the semantic space. The experimental results show the feasibility and applicability of this method.

元の言語English
ホスト出版物のタイトルInformation Modelling and Knowledge Bases XXX
編集者Tatiana Endrjukaite, Hannu Jaakkola, Alexander Dudko, Yasushi Kiyoki, Bernhard Thalheim, Naofumi Yoshida
出版者IOS Press
ページ435-448
ページ数14
ISBN(電子版)9781614999324
DOI
出版物ステータスPublished - 2019 1 1

出版物シリーズ

名前Frontiers in Artificial Intelligence and Applications
312
ISSN(印刷物)0922-6389

ASJC Scopus subject areas

  • Artificial Intelligence

フィンガープリント A correlation computing method for integrating passengers and services in semantic anticipation' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用

    Yokoyama, M., Kiyoki, Y., & Mita, T. (2019). A correlation computing method for integrating passengers and services in semantic anticipation. : T. Endrjukaite, H. Jaakkola, A. Dudko, Y. Kiyoki, B. Thalheim, & N. Yoshida (版), Information Modelling and Knowledge Bases XXX (pp. 435-448). (Frontiers in Artificial Intelligence and Applications; 巻数 312). IOS Press. https://doi.org/10.3233/978-1-61499-933-1-435