Next Article in Journal
Spatiotemporal Variation of Precipitation Regime in China from 1961 to 2014 from the Standardized Precipitation Index
Previous Article in Journal
Initial Results of the Precise Orbit Determination for the New-Generation BeiDou Satellites (BeiDou-3) Based on the iGMAS Network
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessArticle
ISPRS Int. J. Geo-Inf. 2016, 5(11), 195; doi:10.3390/ijgi5110195

Context-Aware Location Recommendation Using Geotagged Photos in Social Media

Research Group Cartography, Vienna University of Technology, Vienna 1040, Austria
Current address: Department of Geography, University of Zurich, Zurich 8057, Switzerland
Academic Editor: Wolfgang Kainz
Received: 18 August 2016 / Revised: 13 October 2016 / Accepted: 23 October 2016 / Published: 28 October 2016
View Full-Text   |   Download PDF [15659 KB, uploaded 28 October 2016]   |  

Abstract

Recently, the increasing availability of digital cameras and the rapid advances in social media have led to the accumulation of a large number of geotagged photos, which may reflect people’s travel experiences in different cities and can be used to generate location recommendations for tourists. Research on this aspect mainly focused on providing personalized recommendations matching a tourist’s travel preferences, while ignoring the context of the visit (e.g., weather, season and time of the day) that potentially influences his/her travel behavior. This article explores context-aware methods to provide location recommendations matching a tourist’s travel preferences and visiting context. Specifically, we apply clustering methods to detect touristic locations and extract travel histories from geotagged photos on Flickr. We then propose a novel context similarity measure to quantify the similarity between any two contexts and develop three context-aware collaborative filtering methods, i.e., contextual pre-filtering, post-filtering and modeling. With these methods, location recommendations like “in similar contexts, other tourists similar to you often visited …” can be provided to the current user. Results of the evaluation with a publicly-available Flickr photo collection show that these methods are able to provide a tourist with location recommendations matching his/her travel preferences and visiting context. More importantly, compared to other state-of-the-art methods, the proposed methods, which employ the introduced context similarity measure, can provide tourists with significantly better recommendations. While Flickr data have been used in this study, these context-aware collaborative filtering (CaCF) methods can also be extended for other kinds of travel histories, such as GPS trajectories and Foursquare check-ins, to provide context-aware recommendations. View Full-Text
Keywords: geotagged photo; location recommendation; context-aware recommendation; collaborative filtering geotagged photo; location recommendation; context-aware recommendation; collaborative filtering
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Huang, H. Context-Aware Location Recommendation Using Geotagged Photos in Social Media. ISPRS Int. J. Geo-Inf. 2016, 5, 195.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top