Discovering Travel Spatiotemporal Pattern Based on Sequential Events Similarity

Joint Authors

Chen, Juanjuan
Huang, Liying
Wang, Chengliang
Zheng, Nijia

Source

Complexity

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-12-29

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Philosophy

Abstract EN

Travel route preferences can strongly interact with the events that happened in networked traveling, and this coevolving phenomena are essential in providing theoretical foundations for travel route recommendation and predicting collective behaviour in social systems.

While most literature puts the focus on route recommendation of individual scenic spots instead of city travel, we propose a novel approach named City Travel Route Recommendation based on Sequential Events Similarity (CTRR-SES) by applying the coevolving spreading dynamics of the city tour networks and mine the travel spatiotemporal patterns in the networks.

First, we present the Event Sequence Similarity Measurement Method based on modelling tourists’ travel sequences.

The method can help measure similarities in various city travel routes, which combine different scenic types, time slots, and relative locations.

Second, by applying the user preference learning method based on scenic type, we learn from the user’s city travel historical data and compute the personalized travel preference.

Finally, we verify our algorithm by collecting data of 54 city travellers of their historical spatiotemporal routes in the ten most popular cities from Mafeng.com.

CTRR-SES shows better performance in predicting the user’s new city travel sequence fitting the user’s individual preference.

American Psychological Association (APA)

Chen, Juanjuan& Huang, Liying& Wang, Chengliang& Zheng, Nijia. 2020. Discovering Travel Spatiotemporal Pattern Based on Sequential Events Similarity. Complexity،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1143085

Modern Language Association (MLA)

Chen, Juanjuan…[et al.]. Discovering Travel Spatiotemporal Pattern Based on Sequential Events Similarity. Complexity No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1143085

American Medical Association (AMA)

Chen, Juanjuan& Huang, Liying& Wang, Chengliang& Zheng, Nijia. Discovering Travel Spatiotemporal Pattern Based on Sequential Events Similarity. Complexity. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1143085

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1143085