Cognitive visualization of popular regions discovered from geo-tagged social media data

Yunzhe Wang, George Baciu, Chenhui Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)14-28
Number of pages15
JournalInternational Journal of Cognitive Informatics and Natural Intelligence
Volume12
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018

Keywords

  • Cognitive visualization
  • Data mining
  • Machine learning
  • Region discovery
  • Semantic analysis
  • Social media

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Artificial Intelligence

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