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Automatic construction of travel itineraries using social breadcrumbs

Published: 13 June 2010 Publication History

Abstract

Vacation planning is one of the frequent---but nonetheless laborious---tasks that people engage themselves with online; requiring skilled interaction with a multitude of resources. This paper constructs intra-city travel itineraries automatically by tapping a latent source reflecting geo-temporal breadcrumbs left by millions of tourists. For example, the popular rich media sharing site, Flickr, allows photos to be stamped by the time of when they were taken and be mapped to Points Of Interests (POIs) by geographical (i.e. latitude-longitude) and semantic (e.g., tags) metadata.
Leveraging this information, we construct itineraries following a two-step approach. Given a city, we first extract photo streams of individual users. Each photo stream provides estimates on where the user was, how long he stayed at each place, and what was the transit time between places. In the second step, we aggregate all user photo streams into a POI graph. Itineraries are then automatically constructed from the graph based on the popularity of the POIs and subject to the user's time and destination constraints.
We evaluate our approach by constructing itineraries for several major cities and comparing them, through a "crowd-sourcing" marketplace (Amazon Mechanical Turk), against itineraries constructed from popular bus tours that are professionally generated. Our extensive survey-based user studies over about 450 workers on AMT indicate that high quality itineraries can be automatically constructed from Flickr data.

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Cited By

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  • (2024)Exploring the potential of Flickr User–Generated Content for Tourism Research: Insights from PortugalEuropean Journal of Tourism, Hospitality and Recreation10.2478/ejthr-2024-001914:2(258-272)Online publication date: 31-Dec-2024
  • (2024)Integrating Traditional and Social Media Data to Predict Bilateral Migrant Stocks in the European UnionInternational Migration Review10.1177/01979183241249969Online publication date: 29-May-2024
  • (2024)An Expectation-Maximization framework for Personalized Itinerary Recommendation with POI Categories and Must-see POIsACM Transactions on Recommender Systems10.1145/36961143:1(1-33)Online publication date: 16-Sep-2024
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      cover image ACM Conferences
      HT '10: Proceedings of the 21st ACM conference on Hypertext and hypermedia
      June 2010
      328 pages
      ISBN:9781450300414
      DOI:10.1145/1810617
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 13 June 2010

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      Author Tags

      1. flickr
      2. geo-tags
      3. mechanical turk
      4. orienteering problem
      5. social media
      6. travel itinerary

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      HT '10: 21st ACM Conference on Hypertext and Hypermedia
      June 13 - 16, 2010
      Ontario, Toronto, Canada

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      Cited By

      View all
      • (2024)Exploring the potential of Flickr User–Generated Content for Tourism Research: Insights from PortugalEuropean Journal of Tourism, Hospitality and Recreation10.2478/ejthr-2024-001914:2(258-272)Online publication date: 31-Dec-2024
      • (2024)Integrating Traditional and Social Media Data to Predict Bilateral Migrant Stocks in the European UnionInternational Migration Review10.1177/01979183241249969Online publication date: 29-May-2024
      • (2024)An Expectation-Maximization framework for Personalized Itinerary Recommendation with POI Categories and Must-see POIsACM Transactions on Recommender Systems10.1145/36961143:1(1-33)Online publication date: 16-Sep-2024
      • (2024)Encoder-Decoder Based Route Generation Model for Flexible Travel RecommendationIEEE Transactions on Services Computing10.1109/TSC.2024.337623117:3(905-920)Online publication date: May-2024
      • (2024)Research on Travel Route Planing Problems Based on Greedy Algorithm2024 4th International Conference on Electronic Information Engineering and Computer Science (EIECS)10.1109/EIECS63941.2024.10800255(755-758)Online publication date: 27-Sep-2024
      • (2024)Including the Temporal Dimension in the Generation of Personalized Itinerary RecommendationsIEEE Access10.1109/ACCESS.2024.344171012(112794-112809)Online publication date: 2024
      • (2024)A survey on personalized itinerary recommendation: From optimisation to deep learningApplied Soft Computing10.1016/j.asoc.2023.111200152(111200)Online publication date: Feb-2024
      • (2024)Recommendation rules to personalize itineraries for tourists in an unfamiliar cityApplied Soft Computing10.1016/j.asoc.2023.111084150(111084)Online publication date: Jan-2024
      • (2024)The bi-objective orienteering problem with hotel selection: an integrated text mining optimisation approachInformation Technology and Management10.1007/s10799-022-00377-525:3(247-275)Online publication date: 1-Sep-2024
      • (2023)National-Level Multimodal Origin–Destination Estimation Based on Passively Collected Location Data and Machine Learning MethodsTransportation Research Record: Journal of the Transportation Research Board10.1177/036119812311897322678:5(525-541)Online publication date: 19-Aug-2023
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