Graph-Based Approach for Personalized Travel Recommendations

Abstract

In the evolving domain of urban mobility systems, the integration of technology with user-centric strategies is pivotal. This research stands on the foundational concept of Mobility-as-a-Service, a user-centric intelligent mobility management distribution system that seeks to prioritize human needs over mere technological infrastructure. The study delves deep into the wealth of data available through mobile sensing technologies, highlighting the unprecedented understanding it offers into human mobility patterns, thus facilitating personalized route recommendations.

Keywords

• mobility-as-a-service
• human mobility patterns
• route recommendation
• bellman-ford’s algorithm
• shortest path