{"type":"ScholarlyArticle","title":"Unsupervised Learning of Semantic Relations between Concepts of a Molecular Biology Ontology","authors":[{"name":"Massimiliano Ciaramita","slug":"massimiliano-ciaramita","given":"Massimiliano","family":"Ciaramita","affiliation":""},{"name":"Aldo Gangemi","slug":"aldo-gangemi","given":"Aldo","family":"Gangemi","affiliation":""},{"name":"Esther Ratsch","slug":"esther-ratsch","given":"Esther","family":"Ratsch","affiliation":""},{"name":"Jasmin Saric","slug":"jasmin-saric","given":"Jasmin","family":"Saric","affiliation":""},{"name":"Isabel Rojas","slug":"isabel-rojas","given":"Isabel","family":"Rojas","affiliation":""}],"abstract":"In this paper we present an unsupervised model for learning arbitrary relations between concepts of a molecular biology ontology for the purpose of supporting text mining and manual ontology building. Relations between named-entities are learned from the GENIA corpus by means of several standard natural language processing techniques. An in-depth analysis of the output of the system shows that the model is accurate and has good potentials for text mining and ontology building applications.","doi":null,"url":"https://ijcai.org/proceedings/2005/178","pdf":"https://ijcai.org/proceedings/2005/0178.pdf","markdown":"https://ijcai.org/proceedings/2005/178.md","bibtex":"https://ijcai.org/proceedings/2005/bibtex/178","volume":{"slug":"2005","title":"Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2005","url":"https://ijcai.org/proceedings/2005/","year":2005,"location":"Edinburgh, Scotland, UK","dates":"","editors":"","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":178,"pages":{"first":659,"last":663},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}