A Context-Aware Route Finding Algorithm for Self-Driving Tourists Using Ontology

被引：5

作者：

Barzegar, Maryam ^{[1
]}

Sadeghi-Niaraki, Abolghasem ^{[2
,3
]}

Shakeri, Maryam ^{[2
]}

Choi, Soo-Mi ^{[3
]}

机构：

[1] Univ Melbourne, Ctr Spatial Data Infrastruct & Land Adm, Dept Infrastruct Engn, Melbourne, Vic 3010, Australia

[2] KN Toosi Univ Technol, Fac Geodesy & Geomat Engn, Geoinformat Technol Ctr Excellence, Tehran 19697, Iran

[3] Sejong Univ, Dept Comp Sci & Engn, Seoul 143747, South Korea

来源：

ELECTRONICS | 2019年 / 8卷 / 07期

关键词：

touristic trip; business trip; ontology; experience; route finding; KNOWLEDGE; SYSTEM; RECOMMENDATION; FRAMEWORK; INFERENCE; EXAMPLES; URBAN; REUSE;

D O I：

10.3390/electronics8070808

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This study proposed a context-aware ontology-based route finding algorithm for self-driving tourists. In this algorithm, two ontologies-namely drivers' experiences and required tourist services-were used according to tourist requirements. Trips were classified into business and touristic. The algorithm was then compared with Google Maps in terms of travel time and travel length for evaluation. The results showed that the proposed algorithm performed similarly to Google Maps in some cases of business trips and better in other cases, with a maximum 10-min travel time difference. In touristic trips, the capabilities of the proposed algorithm were far better than those of Google Maps.

引用

页数：18

共 37 条

[1] Knowledge map-based web platform to facilitate organizational learning return of experiences [J].