A Travel Route Recommendation System Based on Route Clustering Algorithm Considering Spatial Similarity of Routes

We studied and developed a travel route recommendation system based on a route clustering algorithm. Firstly, we extracted real users’ travel routes from the data accumulated in SNS and built a travel route database. Secondly, we propose a route clustering algorithm that considers the spatial similarity of routes. We applied this algorithm to design the travel route recommendation system. The system can retrieve the travel routes in the database that match the user’s preferences and put similar routes into the same route set by the route clustering algorithm. Eventually, the system will recommend several route sets to the user. Since each route set has different spatial characteristics, users can quickly understand the differences between these routes. We showed the system to 21 graduate students at Yamaguchi University and conducted a questionnaire survey. The survey results show that more than 75% of respondents felt that clustering routes through route clustering algorithms would help them more quickly understand the differences and characteristics of those recommended travel routes.