Article published in:
Lexical semantic approaches to terminology
Edited by Pamela Faber and Marie-Claude L'Homme
[Terminology 20:2] 2014
► pp. 279–303

Clustering for semantic purposes

Exploration of semantic similarity in a technical corpus

This paper presents an innovative approach, within the framework of distributional semantics, for the exploration of semantic similarity in a technical corpus. In complement to a previous quantitative semantic analysis conducted in the same domain of machining terminology, this paper sets out to discover fine-grained semantic distinctions in an attempt to explore the semantic heterogeneity of a number of technical items. Multidimensional scaling analysis (MDS) was carried out in order to cluster first-order co-occurrences of a technical node with respect to shared second-order and third-order co-occurrences. By taking into account the association values between relevant first and second-order co-occurrences, semantic similarities and dissimilarities between first-order co-occurrences could be determined, as well as proximities and distances on a graph. In our discussion of the methodology and results of statistical clustering techniques for semantic purposes, we pay special attention to the linguistic and terminological interpretation.
Keywords: Multidimensional scaling (MDS), distributional semantics, specialized corpora, second-order and third-order co-occurrences, semantic similarity
Published online: 31 October 2014
https://doi.org/10.1075/term.20.2.07ber
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