Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
11-2017
Abstract
Exploratory analysis of a text corpus is an important task that can be aided by informative visualization. One spatially-oriented form of document visualization is a scatterplot, whereby every document is associated with a coordinate, and relationships among documents can be perceived through their spatial distances. Semantic visualization further infuses the visualization space with latent semantics, by incorporating a topic model that has a representation in the visualization space, allowing users to also perceive relationships between documents and topics spatially. We illustrate how a semantic visualization system called SemVis could be used to navigate a text corpus interactively and topically via browsing and searching.
Keywords
interactive topical analysis, topic model, semantic visualization
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
CIKM '17: Proceedings of the ACM Conference on Information and Knowledge Management: Singapore, November 6-10
First Page
2487
Last Page
2490
ISBN
9781450349185
Identifier
10.1145/3132847.3133181
Publisher
ACM
City or Country
New York
Citation
LE VAN MINH TUAN and LAUW, Hady Wirawan.
SemVis: Semantic visualization for interactive topical analysis. (2017). CIKM '17: Proceedings of the ACM Conference on Information and Knowledge Management: Singapore, November 6-10. 2487-2490.
Available at: https://ink.library.smu.edu.sg/sis_research/3882
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3132847.3133181
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons
