Visualization of temporal text collections based on Correspondence Analysis
| Autor: | Jean-Hugues Chauchat, Bojana Dalbelo Bašić, Artur Šilić, Annie Morin |
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| Přispěvatelé: | Faculty of Electrical Engineering and Computing [Zagreb] (FER), University of Zagreb, Multimedia content-based indexing (TEXMEX), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), Equipe de Recherche en Ingénierie des Connaissances (ERIC), Université Lumière - Lyon 2 (UL2), suite projet EGIDE Lyon2-Zagreb, Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique |
| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: |
Computer science
Text analytics 02 engineering and technology Singular Value Decomposition Correspondence analysis Clustering information visualization singular value decomposition clustering text analytics Information visualization Text mining [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] Artificial Intelligence Robustness (computer science) 0202 electrical engineering electronic engineering information engineering Cluster analysis Information retrieval business.industry General Engineering Centroid 020207 software engineering Computer Science Applications Temporal database Visualization Data set 020201 artificial intelligence & image processing business |
| Zdroj: | Expert Systems with Applications Expert Systems with Applications, Elsevier, 2012, 39 (15), pp.12143-12157. ⟨10.1016/j.eswa.2012.04.040⟩ Expert Systems with Applications, 2012, 39 (15), pp.12143-12157. ⟨10.1016/j.eswa.2012.04.040⟩ |
| ISSN: | 0957-4174 |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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