摘要：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 modeled 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. Following a review of approaches adopted in the analysis of filmscript we look at how similar approaches can be applied to the scholarly literature.
关键词：Correspondence Analysis, hierarchical clustering, contiguity constrained clustering, text analysis
