Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/79769
Title: Cognitive visualization of popular regions discovered from geo-tagged social media data
Authors: Wang, YZ 
Baciu, G 
Li, CH 
Keywords: Cognitive Visualization
Data Mining
Machine Learning
Region Discovery
Semantic Analysis
Social Media
Issue Date: 2018
Publisher: IGI Global
Source: International journal of cognitive informatics and natural intelligence, Jan.-Mar. 2018, v. 12, no. 1, p. 14-28 How to cite?
Journal: International journal of cognitive informatics and natural intelligence 
Abstract: This article focuses on the cognitive exploration of photo sharing data which contain information about the location where the photo was taken and potentially some description about the photo. Therefore, the features of photo-spots can be deduced. Spots with similar features constitute a region of cognitive interest. The objective is to identify these regions and allow users to explore into regions of interest by cognitive understanding of their features. The authors propose an approach that makes use of semantic analysis, data clustering, and cognitive visualization. In this article, the authors introduce the design of an interactive visualization interface which projects photo sharing data to cognitive social activity map components. The contributions are two-fold. First, the authors put forward a novel social-media data classification method. Second, the authors suggest a new method to explore social activity maps by discovering regions of cognitive interest. Experiments are performed on the Flickr dataset.
URI: http://hdl.handle.net/10397/79769
ISSN: 1557-3958
EISSN: 1557-3966
DOI: 10.4018/IJCINI.2018010102
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