I-VEST: Intelligent visual email search and triage

Jay Koven, Enrico Bertini, Nasir Memon, R. Luke Dubois

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Lawyers and investigators are often presented with large email datasets that contain emails that are not all relevant to any given investigative search. They must often manually comb through information contained within these large datasets in order to find the information they need, expending large amounts of time and money in the process. Our work offers an interactive visual analytic alternative to current methodology. We introduce a method for reducing the number of emails that need to be viewed in a large dataset while also giving the user a quick overview of possible contents and relationships in a set of results.

Original languageEnglish (US)
Title of host publication2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014 - Proceedings
EditorsMin Chen, David Ebert, Chris North
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages257-258
Number of pages2
ISBN (Electronic)9781479962273
DOIs
StatePublished - Feb 13 2015
Event2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014 - Paris, France
Duration: Oct 9 2014Oct 14 2014

Publication series

Name2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014 - Proceedings

Other

Other2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014
Country/TerritoryFrance
CityParis
Period10/9/1410/14/14

Keywords

  • Data Analytics
  • Email Search
  • Investigative Analysis
  • Unstructured Data
  • Visual Analytics

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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