Youjie Zhou
Jiebo Luo
ABSTRACT
The fast evolution and adoption of social media creates an increasingly need for location based services. Location inference on news or events becomes an essential problem. This paper addresses the problem by extracting location involved topics (geo-topic) using both text content and visual content. This paper proposes a geo-topic extraction framework for geo-location inference, including location name entity recognition, location related image association and a multimodal location dependent pLSA geo-topic model. Experiments have shown that our fused model improves the f-score in geo-location inference by 10% compared with single modality based models.
- E. Amitay, N. Har'El, R. Sivan, and A. Soffer. Web-a-where: geotagging web content. In Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR'04, pages 273--280, New York, NY, USA, 2004. ACM. Google Scholar
Digital Library
- R. F. Antonio Torralba and W. T. Freeman. Tiny images mit-csail-tr-2007-024. Technical report, MIT Computer Science and Artificial Intelligence Laboratory, 4 2007.Google Scholar
- L. Cao, J. Yu, J. Luo, and T. S. Huang. Enhancing semantic and geographic annotation of web images via logistic canonical correlation regression. In Proceedings of the 17th ACM international conference on Multimedia, MM '09, pages 125--134, New York, NY, USA, 2009. ACM. Google ScholarDigital Library
- M. Cristani, A. Perina, U. Castellani, and V. Murino. Geo-located image analysis using latent representations. In Proc. IEEE Conf. Computer Vision and Pattern Recognition CVPR 2008, pages 1--8, 2008.Google ScholarCross Ref
- J. Ding, L. Gravano, and N. Shivakumar. Computing geographical scopes of web resources. In Proceedings of the 26th International Conference on Very Large Data Bases, VLDB '00, pages 545--556, San Francisco, CA, USA, 2000. Morgan Kaufmann Publishers Inc. Google ScholarDigital Library
- A. Gallagher, D. Joshi, J. Yu, and J. Luo. Geo-location inference from image content and user tags. In Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition Workshops CVPR Workshops 2009, pages 55--62, 2009.Google ScholarCross Ref
- J. Hays and A. A. Efros. IM2GPS: estimating geographic information from a single image. In Proceedings of the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2008.Google ScholarCross Ref
- T. Hofmann. Probabilistic latent semantic indexing. In Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '99, pages 50--57, New York, NY, USA, 1999. ACM. Google ScholarDigital Library
- D. Joshi, A. Gallagher, J. Yu, and J. Luo. Exploring user image tags for geo-location inference. In Proc. IEEE Int Acoustics Speech and Signal Processing (ICASSP) Conf, pages 5598--5601, 2010.Google ScholarCross Ref
- L. Kennedy, M. Naaman, S. Ahern, R. Nair, and T. Rattenbury. How flickr helps us make sense of the world: context and content in community-contributed media collections. In Proceedings of the 15th international conference on Multimedia, MULTIMEDIA '07, pages 631--640, New York, NY, USA, 2007. ACM. Google ScholarDigital Library
- J. D. Lafferty, A. McCallum, and F. C. N. Pereira. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proceedings of the Eighteenth International Conference on Machine Learning, ICML '01, pages 282--289, San Francisco, CA, USA, 2001. Morgan Kaufmann Publishers Inc. Google ScholarDigital Library
- A. McCallum and W. Li. Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons. In Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4, CONLL '03, pages 188--191, Stroudsburg, PA, USA, 2003. Association for Computational Linguistics. Google ScholarDigital Library
- A. Oliva and A. Torralba. Building the gist of a scene: the role of global image features in recognition. In Progress in Brain Research, page 2006, 2006.Google Scholar
- Z. Yin, L. Cao, J. Han, C. Zhai, and T. Huang. Geographical topic discovery and comparison. In Proceedings of the 20th international conference on World wide web, WWW '11, pages 247--256, New York, NY, USA, 2011. ACM. Google ScholarDigital Library
Index Terms
- Geo-location inference on news articles via multimodal pLSA
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