Visualization of temporal text collections based on Correspondence Analysis

Arthur Šilić 1, * Annie Morin 2 Jean-Hugues Chauchat 3 Bojana Dalbelo Bašić 1
* Corresponding author
2 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : In this paper, we present CatViz--Temporally-Sliced Correspondence Analysis Visualization. This novel method visualizes relationships through time and is suitable for large-scale temporal multivariate data. We couple CatViz with clustering methods, whereupon we introduce the concept of final centroid transfer, which enables the correspondence of clusters in time. Although CatViz can be used on any type of temporal data, we show how it can be applied to the task of exploratory visual analysis of text collections. We present a successful concept of employing feature-type filtering to present different aspects of textual data. We performed case studies on large collections of French and English news articles. In addition, we conducted a user study that confirms the usefulness of our method. We present typical tasks of exploratory text analysis and discuss application procedures that an analyst might perform. We believe that CatViz is general and highly applicable to large data sets because of its intuitiveness, effectiveness, and robustness. We expect that it will enable a better understanding of texts in huge historical archives.
Document type :
Journal articles
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-00712590
Contributor : Fabien Rico <>
Submitted on : Wednesday, June 27, 2012 - 1:31:29 PM
Last modification on : Friday, November 16, 2018 - 1:22:18 AM

Identifiers

Citation

Arthur Šilić, Annie Morin, Jean-Hugues Chauchat, Bojana Dalbelo Bašić. Visualization of temporal text collections based on Correspondence Analysis. Expert Systems with Applications, Elsevier, 2012, 39 (15), pp.12143-12157. ⟨10.1016/j.eswa.2012.04.040⟩. ⟨hal-00712590⟩

Share

Metrics

Record views

376