VISUALIZING THE ICA – A CONTENT-BASED APPROACH

In this paper, we present an experiment aimed at visualizing the contents of the ICA conference proceedings. Its main goal is to provide visual means for exploring the topical structure of the cartographic discipline. The source data for our analysis are the proceedings of the 2001 and 2003 ICA meetings, as published on the conference CDs. The first step is to bring them into a semistructured form as XML files, which are then parsed into a relational database. What follows is a series of text transformations, including stemming, stop word removal, and representation of each document as an n-dimensional vector. Those vectors are used to train an artificial neural network. A number of transformations of geometric and attribute data finally lead to map-like visualizations of ICA conference papers. In this paper, we discuss the methodology and its implementation in detail, interpret some of the major observed patterns, and comment on a number of issues requiring further research.

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