JoTA: Aligning Multilingual Job Taxonomies through Word Embeddings (Student Abstract)

Autor:	Giabelli, A, Malandri, L, Mercorio, F, Mezzanzanica, M
Přispěvatelé:	Giabelli, A, Malandri, L, Mercorio, F, Mezzanzanica, M
Rok vydání:	2022
Předmět:	word embeddings General Medicine artificial intelligence
Zdroj:	Proceedings of the AAAI Conference on Artificial Intelligence. 36:12955-12956
ISSN:	2374-3468 2159-5399
DOI:	10.1609/aaai.v36i11.21614
Popis:	We propose JoTA (Job Taxonomy Alignment), a domain-independent, knowledge-poor method for automatic taxonomy alignment of lexical taxonomies via word embeddings. JoTA associates all the leaf terms of the origin taxonomy to one or many concepts in the destination one, employing a scoring function, which merges the score of a hierarchical method and the score of a classification task. JoTA is developed in the context of an EU Grant aiming at bridging the national taxonomies of EU countries towards the European Skills, Competences, Qualifications and Occupations taxonomy (ESCO) through AI. The method reaches a 0.8 accuracy on recommending top-5 occupations and a wMRR of 0.72.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d02e56d2f551991872c9949abbb7c11 https://doi.org/10.1609/aaai.v36i11.21614 Zobrazit plný text záznamu