Article
Visual analytics for supporting entity relationship discovery on text data
IEEE International Conference on Intelligence and Security Informatics, ISI 2008 Workshops: PAISI, PACCF, and SOCO 2008, Taipei, Taiwan; 17 June 2008
Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
6-2008
Abstract
To conduct content analysis over text data, one may look out for important named objects and entities that refer to real world instances, synthesizing them into knowledge relevant to a given information seeking task. In this paper, we introduce a visual analytics tool called ER-Explorer to support such an analysis task. ER-Explorer consists of a data model known as TUBE and a set of data manipulation operations specially designed for examining entities and relationships in text. As part of TUBE, a set of interestingness measures is defined to help exploring entities and their relationships. We illustrate the use of ER-Explorer in performing the task of finding associations between two given entities over a text data collection.
Keywords
- Information seeking,
- Interestingness measures,
- visual analytics,
- content analysis,
- text data
ISBN
9783540691365
Identifier
10.1007/978-3-540-69304-8_19
Publisher
Springer Verlag
City or Country
Cham
Copyright Owner and License
Authors
Creative Commons License
Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International
Additional URL
http://doi.org/10.1007/978-3-540-69304-8_19
Citation Information
Hanbo DAI, Ee Peng LIM, Hady W. LAUW and Hwee Hwa PANG. "Visual analytics for supporting entity relationship discovery on text data" IEEE International Conference on Intelligence and Security Informatics, ISI 2008 Workshops: PAISI, PACCF, and SOCO 2008, Taipei, Taiwan; 17 June 2008 Vol. 5075 (2008) p. 183 - 194 Available at: http://works.bepress.com/hweehwa-pang/16/