The Computer Journal Advance Access published online on September 9, 2008
The Computer Journal, doi:10.1093/comjnl/bxn045
The Correspondence Analysis Platform for Uncovering Deep Structure in Data and Information
Science Foundation Ireland, Wilton Place, Dublin 2, Ireland
Department of Computer Science, Royal Holloway, University of London, Egham TW20 0EX, England
* Corresponding author: fmurtagh{at}acm.org
Received 7 July 2008; revised 13 August 2008
We study two aspects of information semantics: (i) the collection of all relationships, (ii) tracking and spotting anomaly and change. The first is implemented by endowing all relevant information spaces with a Euclidean metric in a common projected space. The second is modelled by an induced ultrametric. A very general way to achieve a Euclidean embedding of different information spaces based on cross-tabulation counts (and from other input data formats) is provided by correspondence analysis. From there, the induced ultrametric that we are particularly interested in takes a sequential—e.g. temporal—ordering of the data into account. We employ such a perspective to look at narrative, ‘the flow of thought and the flow of language’ (Chafe). In application to policy decision making, we show how we can focus analysis in a small number of dimensions.
Key Words: pattern recognition • content analysis • indexing • artificial intelligence
1 The Sixth Annual Boole Lecture in Informatics. The Annual Boole Lecture was established and is sponsored by the Boole Centre for Research in Informatics, the Cork Constraint Computation Centre, the Department of Computer Science and the School of Mathematical Sciences, at University College Cork. The series is named in honour of George Boole, the first professor of Mathematics at UCC, whose seminal work on logic in the mid-1800s is central to modern digital computing.