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PathRec: visual analysis of travel route recommendations

Version 2 2024-06-06, 12:07
Version 1 2017-07-20, 21:55
conference contribution
posted on 2024-06-06, 12:07 authored by D Chen, D Kim, L Xie, M Shin, AK Menon, CS Ong, I Avazpour, J Grundy
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.

History

Pagination

364-365

Location

Como, Italy

Start date

2017-08-27

End date

2017-08-31

ISBN-13

9781450346528

Language

eng

Publication classification

E Conference publication, E1 Full written paper - refereed

Copyright notice

2017, ACM

Editor/Contributor(s)

[Unknown]

Title of proceedings

RecSys'17 : Proceedings of the Eleventh ACM Conference on Recommender Systems

Event

ACM Recommender Systems. Conference (11th : 2017 : Como, Italy)

Publisher

ACM

Place of publication

New York, N.Y.

Series

ACM Conference on Recommender Systems