Communities of Related Terms in a Karst Terminology Co-occurrence Network

• Dragana Miljkovic ^[1] ; Jan Kralj ^[1] ; Uroš Stepišnik ^[2] ; Senja Pollak ^[1]
  1. [1] Jožef Stefan Institute

     Jožef Stefan Institute

     Eslovenia

     
  2. [2] University of Ljubljana

     University of Ljubljana

     Eslovenia

     
• Localización: Electronic lexicography in the 21st century. Proceedings of the eLex 2019 conference. 1-3 October 2019, Sintra, Portugal / Iztok Kosem (ed. lit.), Tanara Zingano Kuhn (ed. lit.), Margarita Correia (ed. lit.), José Pedro Ferreira (ed. lit.), Maarten Jansen (ed. lit.), Isabel Pereira (ed. lit.), Jelena Kallas (ed. lit.), Miloš Jakubíček (ed. lit.), Simon Krek (ed. lit.), Carole Tiberius (ed. lit.), 2019, págs. 357-373
• Idioma: inglés
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• Resumen

  • Karst science is an attractive field of interdisciplinary research with rich terminology. This study was performed as part of a project aiming at developing novel approaches to terminology extraction and visualization, in line with the understanding of knowledge, as represented in texts, as conceptually dynamic and linguistically varied. The aim of this paper is to investigate how powerful graph-based methods can be used for visualizing and analysing domain terminology. In order to detect communities in karst terminology, we analyse the frequently co- occurring karst terms in a scientific corpus of karstologic literature. The most frequent co- occurrence pairs, which included ten or more co-occurrences within the whole corpus, are delivered as input to the Louvain community detection algorithm and visualized as a domain graph. The resulting data was evaluated by domain experts who found that the detected term groups are meaningful and correspond to different types of karst phenomena. The results are further discussed in relation to more standard topic modelling approaches, using Latent Dirichlet Allocation and Non-negative Matrix Factorization algorithms.