{"type":"ScholarlyArticle","title":"A Human-AI Teaming Approach for Incremental Taxonomy Learning from Text","authors":[{"name":"Andrea Seveso","slug":"andrea-seveso","given":"Andrea","family":"Seveso","affiliation":""},{"name":"Fabio Mercorio","slug":"fabio-mercorio","given":"Fabio","family":"Mercorio","affiliation":""},{"name":"Mario Mezzanzanica","slug":"mario-mezzanzanica","given":"Mario","family":"Mezzanzanica","affiliation":""}],"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.","doi":"10.24963/ijcai.2021/690","url":"https://ijcai.org/proceedings/2021/690","pdf":"https://ijcai.org/proceedings/2021/0690.pdf","markdown":"https://ijcai.org/proceedings/2021/690.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/690","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":690,"pages":{"first":4917,"last":4918},"keywords":["Data Mining: Recommender Systems","Knowledge Representation and Reasoning: Semantic Web","Natural Language Processing: Knowledge Extraction","Humans and AI: Human-AI Collaboration"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}