An intelligent and context-aware touring system based on ontology

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

With the explosive development of mobile applications, users can find a tremendous amount of travel information with just a few phone taps. However, from the perspective of information quality, most applications lack a well-organized structure that can fit various user needs. On the other hand, it is also important to consider the cultural and historical characteristics of the visited sites, in addition to focusing on sightseeing. The reason is that there are often some specific relationships among the sites. For example, many temples in Taiwan are branched from a root temple. Thus, the presented information should not be limited to a single site at a single time point. A mechanism that can help users to get the desired information more effectively and efficiently is preferred. In this paper, we are going to present an intelligent and context-aware touring system by developing an active recommendation mechanism and application. We will adopt ontology to construct the temporal, spatial, and causality relationships among the tourist attractions. Then, a personalized recommendation mechanism will be developed by integrating context-aware and data mining techniques to make recommendation decisions and “push” the information to the user’s mobile devices. In this way, users can get the most appropriate information while sightseeing.

原文English
主出版物標題HCI International 2018 – Posters’ Extended Abstracts - 20th International Conference, HCI International 2018, Proceedings
編輯Constantine Stephanidis
發行者Springer Verlag
頁面452-457
頁數6
ISBN(列印)9783319922690
DOIs
出版狀態Published - 2018 一月 1
事件20th International Conference on HCI, HCI International 2018 - Las Vegas, United States
持續時間: 2018 七月 152018 七月 20

出版系列

名字Communications in Computer and Information Science
850
ISSN(列印)1865-0929

Conference

Conference20th International Conference on HCI, HCI International 2018
國家United States
城市Las Vegas
期間18-07-1518-07-20

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

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