Deep Learning and Natural Language Processing in the Field of Construction

Rémy Kessler; Nicolas Béchet

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arXiv · 2501.07911

Deep Learning and Natural Language Processing in the Field of Construction

Rémy Kessler·Nicolas Béchet

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Abstract

This article presents a complete process to extract hypernym relationships in the field of construction using two main steps: terminology extraction and detection of hypernyms from these terms. We first describe the corpus analysis method to extract terminology from a collection of technical specifications in the field of construction. Using statistics and word n-grams analysis, we extract the domain's terminology and then perform pruning steps with linguistic patterns and internet queries to improve the quality of the final terminology. Second, we present a machine-learning approach based on various words embedding models and combinations to deal with the detection of hypernyms from the extracted terminology. Extracted terminology is evaluated using a manual evaluation carried out by 6 experts in the domain, and the hypernym identification method is evaluated with different datasets. The global approach provides relevant and promising results.

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Rémy Kessler, Nicolas Béchet. 2025-01-14. Deep Learning and Natural Language Processing in the Field of Construction. https://arxiv.org/abs/2501.07911

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