Time-sensitive Travel Route Recommendations

DOI

10.2991/emim-18.2018.29How to use a DOI?

Keywords

Route recommendation; Time-sensitive; Transition graph model; Check-in data; Hierarchical clustering

Abstract

With the rapid development of mobile Internet and the widespread use of mobile devices, social networking platforms such as Gowalla and Foursquare provide sign-in sharing capabilities. They use these functions to collect a large number of check-in data that can reflect the user's travel patterns. These data can effectively support the recommendation and search of travel routes. This paper studies the recommendation of tourist routes for the change of scenic spots popularity caused by time change in spatial area. We quantitatively represent the changes in the popularity of the locations in the region in the form of time series, and recommend the travel routes that are most suitable for the travel time of the users. The route recommendation of the dynamic transition graph mode can be used for tourism route recommendation, scenic area construction, and safe facility deployment. The proposed dynamic transition graph model was constructed with real data sets and sufficient experiments were conducted. It is verified that under the condition of different parameters, the user's income in the recommended route is higher than the existing work by over 10%. This verifies the accuracy and effectiveness of the proposed method.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huanliang Sun
AU  - Dacheng Ye
AU  - Junling Liu
PY  - 2018/08
DA  - 2018/08
TI  - Time-sensitive Travel Route Recommendations
BT  - Proceedings of the 8th International Conference on Education, Management, Information and Management Society (EMIM 2018)
PB  - Atlantis Press
SP  - 137
EP  - 142
SN  - 2352-5398
UR  - https://doi.org/10.2991/emim-18.2018.29
DO  - 10.2991/emim-18.2018.29
ID  - Sun2018/08
ER  -