Knowledge Mining With VxInsight: Discovery ThroughInteraction
Journal of Intelligent Information Systems - Special issue on information visualization: the next frontier
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
A Dynamic Probabilistic Model to Visualise Topic Evolution in Text Streams
Journal of Intelligent Information Systems
ThemeRiver: Visualizing Theme Changes over Time
INFOVIS '00 Proceedings of the IEEE Symposium on Information Vizualization 2000
Visualizing Live Text Streams Using Motion and Temporal Pooling
IEEE Computer Graphics and Applications
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Out-of-core SVD performance for document indexing
Applied Numerical Mathematics
Sequential Document Visualization
IEEE Transactions on Visualization and Computer Graphics
NewsLab: Exploratory Broadcast News Video Analysis
VAST '07 Proceedings of the 2007 IEEE Symposium on Visual Analytics Science and Technology
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Textual features for corpus visualization using correspondence analysis
Intelligent Data Analysis
Visualization of text streams: a survey
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Dynamic visualization of transient data streams
INFOVIS'03 Proceedings of the Ninth annual IEEE conference on Information visualization
STREAMIT: Dynamic visualization and interactive exploration of text streams
PACIFICVIS '11 Proceedings of the 2011 IEEE Pacific Visualization Symposium
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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.