Author： Bavaud François Xanthos Aris
Publisher： Routledge Ltd
ISSN： 0929-6174
Source： Journal of Quantitative Linguistics, Vol.12, Iss.2-3, 2005-12, pp. : 123-137
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Abstract
Quantifying the concept of co-occurrence and iterated co-occurrence yields indices of similarity between words or between documents. These similarities are associated with a reversible Markov transition matrix, the formal properties of which enable us to define euclidean distances, allowing in turn to perform words-documents correspondence analysis as well as words (or documents) classifications at various co-occurrences orders.
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