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Scientific Programming
Volume 2016 (2016), Article ID 5283471, 7 pages
http://dx.doi.org/10.1155/2016/5283471
Research Article

Topic Modeling Based Image Clustering by Events in Social Media

1Computing Center, Northeastern University, Liaoning 11089, China
2School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK 74078, USA
3College of Information Science and Engineering, Northeastern University, Liaoning 11089, China

Received 16 May 2016; Revised 16 August 2016; Accepted 29 September 2016

Academic Editor: Fabrizio Messina

Copyright © 2016 Bin Xu et al. 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.

Abstract

Social event detection in large photo collections is very challenging and multimodal clustering is an effective methodology to deal with the problem. Geographic information is important in event detection. This paper proposed a topic model based approach to estimate the missing geographic information for photos. The approach utilizes a supervised multimodal topic model to estimate the joint distribution of time, geographic, content, and attached textual information. Then we annotate the missing geographic photos with a predicted geographic coordinate. Experimental results indicate that the clustering performance improved by annotated geographic information.