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Article
Publication date: 1 January 1996

SÁNDOR DARÁNYI, ROBERT ZAWIASA and ZOLTÁN HAJNAL

The idea of conceptual mapping goes back to the semantic differential and conceptual clustering. Using multivariate statistical techniques, one can map a dispersion of texts onto…

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Abstract

The idea of conceptual mapping goes back to the semantic differential and conceptual clustering. Using multivariate statistical techniques, one can map a dispersion of texts onto another dispersion of their content indicators, such as keywords. The resulting configurations of texts/indicators differ from one another according to their meaning, expressed in terms of co‐ordinates of a semantic field. We suggest that by using principal component analysis, one can design a user‐friendly semantic space which can be navigated. Further, to learn the names of embedded magnitudes in semantic space, the idea of conceptual clustering is used in a broader context. This is a two‐mode statistical approach, grouping both documents and their index terms at the same time. By observing the agglomerations of narrower, related terms over a corpus, one arrives at broader, more general thesaurus entries which denote and conceptualise the major dimensions of semantic space.

Details

Journal of Documentation, vol. 52 no. 1
Type: Research Article
ISSN: 0022-0418

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