PathRec: Visual Analysis of Travel Route Recommendations
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 6 Jul 2017.
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- 2021Learning to Route via Theory-Guided Residual Networkcited by 0
- 2021Learning to Route via Theory-Guided Residual Network18 May 2021