---
title: "Unsupervised Learning of Semantic Relations between Concepts of a Molecular Biology Ontology"
authors:
  - "Massimiliano Ciaramita"
  - "Aldo Gangemi"
  - "Esther Ratsch"
  - "Jasmin Saric"
  - "Isabel Rojas"
doi: ""
url: "https://ijcai.org/proceedings/2005/178"
pdf: "https://ijcai.org/proceedings/2005/0178.pdf"
venue: "Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence"
year: 2005
pages: "659-663"
track: ""
keywords:
---

# Unsupervised Learning of Semantic Relations between Concepts of a Molecular Biology Ontology

Massimiliano Ciaramita, Aldo Gangemi, Esther Ratsch, Jasmin Saric, Isabel Rojas

*Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence*, pages 659-663.

## 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.