Paper Info
Title
Tour-Route-Recommendation Algorithm Based on the Improved AGNES Spatial Clustering and Space-Time Deduction Model
Abstract
This study designed a tour-route-planning and recommendation algorithm that was based on an improved AGNES spatial clustering and space-time deduction model. First, the improved AGNES tourist attraction spatial clustering algorithm was created. Based on the features and spatial attributes, city tourist attraction clusters were formed, in which the tourist attractions with a high degree of correlation among attributes were gathered into the same cluster. It formed the precondition for searching tourist attractions that would match tourist interests. Using tourist attraction clusters, this study also developed a tourist attraction reachability model that was based on tourist-interest data and geospatial relationships to confirm each tourist attraction's degree of correlation to tourist interests. A dynamic space-time deduction algorithm that was based on travel time and cost allowances was designed in which the transportation mode, time, and costs were set as the key factors. To verify the proposed algorithm, two control algorithms were chosen and tested against the proposed algorithm. Our results showed that the proposed algorithm had better results for tour-route planning under different transportation modes as compared to the controls. The proposed algorithm not only considered time and cost allowances, but it also considered the shortest traveling distance between tourist attractions. Therefore, the tourist attractions and tour routes that were suggested not only met tourist interests, but they also conformed to the constraint conditions and lowered the overall total costs.
Year
DOI
Venue
2022
10.3390/ijgi11020118
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Keywords
DocType
Volume
AGNES clustering, tourist attraction clustering, tourist attraction reachability space model, space-time deduction, tour route searching
Journal
11
Issue
ISSN
Citations 
2
2220-9964
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Xiao Zhou100.68
Jiangpeng Tian200.68
Mingzhan Su311.36