PathRec: Visual Analysis of Travel Route Recommendations

TL;DR

PathRec is an interactive visualization tool that leverages new machine learning algorithms to recommend travel routes, helping users understand and compare different trajectory options through detailed visual analysis.

Contribution

The paper introduces a novel visual system for travel route recommendation that incorporates new ML formulations and supports detailed feature-based analysis of trajectories.

Findings

Effective visualization aids user decision-making.

System can compare multiple route features simultaneously.

Design principles applicable to other structured prediction visualizations.

Abstract

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.