User-driven assessment of commercial term extractors

Autor:	Oi Yee Kwong
Rok vydání:	2021
Předmět:	Computer science business.industry End user Communication Perspective (graphical) Variation (game tree) Benchmarking Library and Information Sciences Data science Popularity Language and Linguistics Term (time) User driven User experience design business
Zdroj:	Terminology. 27:179-218
ISSN:	1569-9994 0929-9971
DOI:	10.1075/term.20032.kwo
Popis:	In this paper, we address the system evaluation issue for commercial term extraction tools from the users’ perspective. We first revisit the gold standard approach commonly practised among researchers, and discuss the challenges it may pose on end users, taking translators as a typical example. Considering the very different motivations and needs of users and researchers, a user-driven approach is proposed as a variation and alternative to the gold standard approach to allow users to assess and understand the performance of commercial tools more objectively. Its feasibility and usefulness are demonstrated by deploying a benchmarking dataset of English-Chinese financial terms, produced by multiple annotators, in a case study with SDL MultiTerm Extract. The results also provide insight for future development of term extractors designed for translators, which will hopefully generate more accurate candidates, offer more customised features, enable better user experience, and enjoy wider popularity as a computer-aided translation tool.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::675b821a21808a8f4139120e779717ed https://doi.org/10.1075/term.20032.kwo Zobrazit plný text záznamu