Using NLP to support terminology extraction and domain scoping: report on the H2020 DESIRA project

Bacco F. M., Brunori G., Dell'Orletta F., Ferrari A.

NLP  WIkipedia  Socio-economic impact  Taxonomy  Knowledge graph  Terminology extraction  Domain scoping 

The ongoing phenomenon of digitisation is changing social and work life, with tangible effects on the socio-economic context. Understanding the impact, opportunities, and threats of digital transformation requires the identication of viewpoints from a large diversity of stakeholders, from policy makers to domain experts, and from engineers to common citizens. The DESIRA (Digitisation: Economic and Social Impacts in Rural Areas) EU H2020 project1 considers rural areas, with a strong focus on agricultural and forestry activities, and aims at assessing the impact of digital technologies in those domains by involving a large number of stakeholders, all across Europe, around 20 focal questions. Given the involvement of stakeholders with diverse background and skills, a primary goal of the project is to develop domain-specic and interactive reference taxonomies (i.e., structured classications of terms) to facilitate common understanding of technologies in use in each domain at today. The taxonomies, which aims at easing the learning of the meaning of technical and domain-specic terms, are going to be exploited by the stakeholders in 20 Living Labs built around the focal questions. This report paper focuses on the semi-automatic development of the taxonomies through natural language processing (NLP) techniques based on context-specic term extraction. Furthermore, we crawl Wikipedia to enrich the taxonomies with additional categories and denitions. We plan to validate the taxonomies through fieeld studies within the Living Labs.

Source: Third Workshop on Natural Language Processing for Requirements Engineering, pp. 1–5, Pisa, Italy, 24 March 2020

Publisher: CEUR-WS.org, Aachen, DEU