DocumentCode
119610
Title
Event-based text visual analytics
Author
Wang, Ji ; Bradel, Lauren ; North, Chris
Author_Institution
Virginia Tech
fYear
2014
fDate
25-31 Oct. 2014
Firstpage
333
Lastpage
334
Abstract
We present an event-based approach for solving a directed sensemaking task in which we combine powerful information foraging tools with intuitive synthesis spaces to solve the VAST Challenge 2014 Mini-Challenge 1. A combination of student-created and commericially available software are used to solve various aspects of the scenario. In addition to applying entitiy extraction and topic modelling, we enable the user to explore a large dataset using multi-model semantic interaction, which infers analytical reasoning from user actions to augment the data spatialization and determine what information should be presented and suggested to the user. Additionally, we visualize extracted topics using Tableau to construct a timeline of events surrounding the questions posed by the challenge.
Keywords
Sensemaking; event extraction; semantic interaction; topic modelling;
fLanguage
English
Publisher
ieee
Conference_Titel
Visual Analytics Science and Technology (VAST), 2014 IEEE Conference on
Conference_Location
Paris, France
Type
conf
DOI
10.1109/VAST.2014.7042552
Filename
7042552
Link To Document