Mining Context-Aware Significant Travel Sequences from Geotagged Social Media

Abdul Majid, Ling Chen, Hamid Turab Mirza, Ibrar Hussain, Gencai Chen

AAAI 2012 pp. 2443-2444

doi:10.1609/AAAI.V26I1.8407 /aaai/2012/majid2012aaai-mining/

Abstract

Geotagged photos of users on social media site, i.e., Flickr provide plentiful location-based data, which has been exploited for location-based services, such as mapping geotags to places and recommendation of personalized landmarks. As users’ preferences to visit a location or multiple locations in a certain sequence could be affected by their current temporal, and weather context. This paper considers the problem of mining context-aware significant semantic travel sequences from geotagged photos.

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Cite

Text

Majid et al. "Mining Context-Aware Significant Travel Sequences from Geotagged Social Media." AAAI Conference on Artificial Intelligence, 2012. doi:10.1609/AAAI.V26I1.8407

Markdown

[Majid et al. "Mining Context-Aware Significant Travel Sequences from Geotagged Social Media." AAAI Conference on Artificial Intelligence, 2012.](https://mlanthology.org/aaai/2012/majid2012aaai-mining/) doi:10.1609/AAAI.V26I1.8407

BibTeX

@inproceedings{majid2012aaai-mining,
  title     = {{Mining Context-Aware Significant Travel Sequences from Geotagged Social Media}},
  author    = {Majid, Abdul and Chen, Ling and Mirza, Hamid Turab and Hussain, Ibrar and Chen, Gencai},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2012},
  pages     = {2443-2444},
  doi       = {10.1609/AAAI.V26I1.8407},
  url       = {https://mlanthology.org/aaai/2012/majid2012aaai-mining/}
}