Topic-based coordination for visual analysis of evolving document collections

Document interpretation is a crucial task in many visual analytics applications, made harder by the widespread availability of freely available textual files. In this paper we propose an approach based on topic detection coupled with multiple coordinated views to assist analysis of time varying document collections. Given multiple document maps built from a set of text files, we define a strategy to support users locating the evolution of topics addressed by the documents, along various time steps. The approach is supported by a new algorithm for topic extraction from texts, also introduced. Finally, we show several examples illustrating how the proposed strategy may be applied in the analysis of document collections.