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Deducing trip related information from flickr

Published: 20 April 2009 Publication History

Abstract

Uploading tourist photos is a popular activity on photo sharing platforms. These photographs and their associated metadata (tags, geo-tags, and temporal information) should be useful for mining information about the sites visited. However, user-supplied metadata are often noisy and efficient filtering methods are needed before extracting useful knowledge. We focus here on exploiting temporal information, associated with tourist sites that appear in Flickr. From automatically filtered sets of geo-tagged photos, we deduce answers to questions like "how long does it take to visit a tourist attraction?" or "what can I visit in one day in this city?" Our method is evaluated and validated by comparing the automatically obtained visit duration times to manual estimations.

References

[1]
Girardin, F., Dal Fiore, F., Blat, J., Ratti, C. Understanding of Tourist Dynamics from Explicitly Disclosed Location Information. In Proc. of the 4th International Symposium on LBS and Telecartography (Hong-Kong, China, 2007).
[2]
Homeandabroad -- http://homeandabroad.com
[3]
Popescu, A., Grefenstette, G., Moëllic, P.-A. Gazetiki: automatic construction of a geographical gazetteer. In Proc. of JCDL 2008 (Pittsburgh, PA, June 2008).
[4]
Rattenbury, T., Good, N., Naaman, M. 2007. Towards Automatic Extraction of Event and Place Semantics from Flickr Tags. In Proc. of SIGIR 2007 (Amsterdam, The Netherlands, July 2007).

Cited By

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  • (2023)TourismNLG: A Multi-lingual Generative Benchmark for the Tourism DomainAdvances in Information Retrieval10.1007/978-3-031-28244-7_10(150-166)Online publication date: 17-Mar-2023
  • (2021)Discovering shopping visitors’ behavior and preferences using geo-tagged social photos: a case study of Los Angeles CityJournal of Marketing Analytics10.1057/s41270-021-00107-wOnline publication date: 23-Feb-2021
  • (2021)Should I Visit This Place? Inclusion and Exclusion Phrase Mining from ReviewsAdvances in Information Retrieval10.1007/978-3-030-72240-1_27(287-294)Online publication date: 30-Mar-2021
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  1. Deducing trip related information from flickr

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    cover image ACM Conferences
    WWW '09: Proceedings of the 18th international conference on World wide web
    April 2009
    1280 pages
    ISBN:9781605584874
    DOI:10.1145/1526709

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 20 April 2009

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    Author Tags

    1. flickr
    2. geographical gazetteer
    3. georeferencing
    4. image mining
    5. text mining
    6. tourist sites
    7. visit times

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    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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    View all
    • (2023)TourismNLG: A Multi-lingual Generative Benchmark for the Tourism DomainAdvances in Information Retrieval10.1007/978-3-031-28244-7_10(150-166)Online publication date: 17-Mar-2023
    • (2021)Discovering shopping visitors’ behavior and preferences using geo-tagged social photos: a case study of Los Angeles CityJournal of Marketing Analytics10.1057/s41270-021-00107-wOnline publication date: 23-Feb-2021
    • (2021)Should I Visit This Place? Inclusion and Exclusion Phrase Mining from ReviewsAdvances in Information Retrieval10.1007/978-3-030-72240-1_27(287-294)Online publication date: 30-Mar-2021
    • (2020)Characterizing Tourism Destination Image Using Photos’ Visual ContentISPRS International Journal of Geo-Information10.3390/ijgi91207309:12(730)Online publication date: 7-Dec-2020
    • (2020)Tourist Tracking Techniques as a Tool to Understand and Manage Tourism FlowsOvertourism10.1007/978-3-030-42458-9_6(89-105)Online publication date: 31-May-2020
    • (2019)Geographical Design: Spatial Cognition and Geographical Information ScienceSynthesis Lectures on Human-Centered Informatics10.2200/S00921ED2V01Y201904HCI04312:3(i-69)Online publication date: 16-May-2019
    • (2019)Machine learning and points of interest: typical tourist Italian citiesCurrent Issues in Tourism10.1080/13683500.2019.163782723:13(1646-1658)Online publication date: 12-Jul-2019
    • (2019)Exploiting semantics for context-aware itinerary recommendationPersonal and Ubiquitous Computing10.1007/s00779-018-01189-723:2(215-231)Online publication date: 1-Apr-2019
    • (2018)Can We Predict the Scenic Beauty of Locations from Geo-tagged Flickr Images?Proceedings of the 2018 Conference on Human Information Interaction&Retrieval - IUI '1810.1145/3172944.3173000(653-657)Online publication date: 2018
    • (2018)Geographic Biases are 'Born, not Made'Proceedings of the 2018 ACM International Conference on Supporting Group Work10.1145/3148330.3148350(71-82)Online publication date: 7-Jan-2018
    • Show More Cited By

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