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Visual content correlation analysis

  • Furu Wei*
  • , Lei Shi
  • , Li Tan
  • , Xiaohua Sun
  • , Xiaoxiao Lian
  • , Shixia Liu
  • , Michelle X. Zhou
  • *Corresponding author for this work
  • IBM

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Correlating content from multiple data fields is one of the key challenges in text mining. In this paper, we propose a visual analytics approach that leverages both content correlation analysis and interactive visualization technologies in analyzing and understanding content correlations. We have applied our work to analyzing NHAMCS data (National Hospital Ambulatory Medical Care Survey), which helps reveal healthcare-related data patterns through the correlations between unstructured data fields (e.g., cause of injury and diagnosis) and between structured and unstructured fields (e.g., gender and cause of injury).

Original languageEnglish
Title of host publication1st International Workshop on Intelligent Visual Interfaces for Text Analysis, IVITA'10 - Proceedings
Pages25-28
Number of pages4
DOIs
StatePublished - 2010
Externally publishedYes
Event1st International Workshop on Intelligent Visual Interfaces for Text Analysis, IVITA'10 - Hong Kong, China
Duration: 7 Feb 20107 Feb 2010

Publication series

NameInternational Conference on Intelligent User Interfaces, Proceedings IUI

Conference

Conference1st International Workshop on Intelligent Visual Interfaces for Text Analysis, IVITA'10
Country/TerritoryChina
CityHong Kong
Period7/02/107/02/10

Keywords

  • content correlation
  • visual text analytics
  • visualization

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