Murtagh, Fionn (2010) The Correspondence Analysis Platform for Uncovering Deep Structure in Data and Information. The Computer Journal, 53 (3).
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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.
This is a Submitted version This version's date is: 2010 This item is not peer reviewed
https://repository.royalholloway.ac.uk/items/c926ec7f-5dc5-af7e-6114-86b55beabc1d/5/
Deposited by Research Information System (atira) on 03-Jul-2014 in Royal Holloway Research Online.Last modified on 03-Jul-2014
Sixth Annual Boole Lecture in Informatics, Boole Centre for Research in Informatics, Cork, Ireland, 29 April 2008.