PathRec: Visual Analysis of Travel Route Recommendations
This is an incremental improvement for online map users, potentially benefiting a large cohort by enhancing route planning through visual analysis.
The paper tackles the problem of travel route recommendations by introducing an interactive visualization tool that breaks down contributions from geographical and user behavior features, as well as individual points-of-interest versus pairs of consecutive points, to assist decision-making for online map users.
We present an interactive visualisation tool for recommending travel trajectories. This system is based on new machine learning formulations and algorithms for the sequence recommendation problem. The system starts from a map-based overview, taking an interactive query as starting point. It then breaks down contributions from different geographical and user behavior features, and those from individual points-of-interest versus pairs of consecutive points on a route. The system also supports detailed quantitative interrogation by comparing a large number of features for multiple points. Effective trajectory visualisations can potentially benefit a large cohort of online map users and assist their decision-making. More broadly, the design of this system can inform visualisations of other structured prediction tasks, such as for sequences or trees.