Conference Proceeding Article
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.
interactive topical analysis, topic model, semantic visualization
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
CIKM '17: Proceedings of the ACM Conference on Information and Knowledge Management: Singapore, November 6-10
City or Country
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. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3882
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