Research Article
Mining Ancient Medicine Texts Towards an Ontology of Remedies – A Semi-automatic Approach
@INPROCEEDINGS{10.1007/978-3-031-35081-8_11, author={Jo\"{a}o Nunes and Orlando Belo and Anabela Barros}, title={Mining Ancient Medicine Texts Towards an Ontology of Remedies -- A Semi-automatic Approach}, proceedings={Intelligent Systems and Machine Learning. First EAI International Conference, ICISML 2022, Hyderabad, India, December 16-17, 2022, Proceedings, Part II}, proceedings_a={ICISML PART 2}, year={2023}, month={7}, keywords={Ontology Learning Linguistic Ontologies Extracting Knowledge from Textual Data Natural Language Processing Linguistic Patterns Graph Databases}, doi={10.1007/978-3-031-35081-8_11} }- João Nunes
Orlando Belo
Anabela Barros
Year: 2023
Mining Ancient Medicine Texts Towards an Ontology of Remedies – A Semi-automatic Approach
ICISML PART 2
Springer
DOI: 10.1007/978-3-031-35081-8_11
Abstract
Over the last years, ontology learning processes have gained a vast space for discussion and work, providing essential tools for discovering knowledge, especially from textual information sources. One of the most currently used techniques for extracting ontological elements from textual data is through the application of lexical-syntactic patterns, which aim to explore formalities of the language in which texts are written, for removing hyperonym/hyponym pairs that can be used to identify and characterize ontology concepts and create valuable semantic networks of terms. We applied a lexical-syntactic patterns approach in a set of medicine texts, written in classical Portuguese, during the 16th and 17th centuries, with the goal of extracting hyperonym/hyponym pairs to establish a medicine ontology of the time. In this paper, we discuss the most relevant aspects of an ontology learning system we implemented for extracting the referred ontology, which has the ability for characterizing the knowledge expressed in ancient medicament texts.
