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arXiv · 1707.01627

PathRec: Visual Analysis of Travel Route Recommendations

Dawei Chen·Dongwoo Kim·Lexing Xie·Minjeong Shin·Aditya Krishna Menon·Cheng Soon Ong·Iman Avazpour·John Grundy
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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.

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Dawei Chen, Dongwoo Kim, Lexing Xie, Minjeong Shin, Aditya Krishna Menon, Cheng Soon Ong, Iman Avazpour, John Grundy. 2017-07-06. PathRec: Visual Analysis of Travel Route Recommendations. https://arxiv.org/abs/1707.01627

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