MDP-based itinerary recommendation using geo-tagged social media

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

Planning vacations is a complex decision problem. Many variables like the place(s) to visit, how many days to stay, the duration at each location, and the overall travel budget need to be controlled and arranged by the user. Automatically recommending travel itineraries would thus be a remedy to quickly converge to an individual trip that is tailored to a user’s interests. While on a trip, users frequently share their experiences on social media platforms e.g., by uploading photos of specific locations and times of day. Their uploaded data serves as an asset when it comes to gathering information on their journey. In this paper, we leverage social media, more explicitly photo uploads and their tags, to reverse engineer historic user itineraries. Our solution grounds on Markov decision processes that capture the sequential nature of itineraries. The tags attached to the photos provide the factors to generate possible configurations and prove crucial for contextualising the proposed approach. Empirically, we observe that the predicted itineraries are more accurate than standard path planning algorithms.

OriginalspracheEnglisch
TitelAdvances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, Proceedings
HerausgeberWouter Duivesteijn, Arno Siebes, Antti Ukkonen
Anzahl der Seiten13
ErscheinungsortBasel
VerlagSpringer Nature AG
Erscheinungsdatum25.10.2018
Seiten111-123
ISBN (Print)978-3-030-01767-5
ISBN (elektronisch)978-3-030-01768-2
DOIs
PublikationsstatusErschienen - 25.10.2018
Veranstaltung17th International Symposium on Intelligent Data Analysis - IDA 2018 - ‘s-Hertogenbosch, Niederlande
Dauer: 24.10.201826.10.2018
Konferenznummer: 17
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