Publication Type

Conference Proceeding Article

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

Research Areas

Data Management and Analytics

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

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

https://doi.org/10.1145/3132847.3133181

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