Taxonomies provide a structured representation of semantic relations between lexical terms, acting as the backbone of many applications. The research proposed herein addresses the topic of taxonomy enrichment using an”human-in-the-loop” semi-supervised approach. I will be investigating possible ways to extend and enrich a taxonomy using corpora of unstructured text data. The objective is to develop a methodological framework potentially applicable to any domain.
Seveso, A., Mercorio, F., Mezzanzanica, M. (2021). A Human-AI Teaming Approach for Incremental Taxonomy Learning from Text. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (pp.4917-4918). International Joint Conferences on Artificial Intelligence.
A Human-AI Teaming Approach for Incremental Taxonomy Learning from Text
Seveso A.
;Mercorio F.;Mezzanzanica M.
2021
Abstract
Taxonomies provide a structured representation of semantic relations between lexical terms, acting as the backbone of many applications. The research proposed herein addresses the topic of taxonomy enrichment using an”human-in-the-loop” semi-supervised approach. I will be investigating possible ways to extend and enrich a taxonomy using corpora of unstructured text data. The objective is to develop a methodological framework potentially applicable to any domain.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
