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Authors: Agnieszka Mykowiecka and Malgorzata Marciniak

Affiliation: Polish Academy of Sciences, Poland

Keyword(s): Terminology Extraction, Term Clustering, Medical Data, Ontology.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Domain Analysis and Modeling ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Natural Language Processing ; Pattern Recognition ; Symbolic Systems

Abstract: The paper presents the first results of clustering terms extracted from hospital discharge documents written in Polish. The aim of the task is to prepare data for an ontology reflecting the domain of documents. To begin, the characteristic of the language of texts, which differs significantly from general Polish, is given. Then, we describe the method of term extraction. In the process of finding related terms, we use lexical and syntactical information. We define term similarity based on: term contexts; coordinated sequences of terms; words that are parts of terms, e.g. their heads and modifiers. Then we performed several experiments with hierarchical clustering of the 300 most frequent terms. Finally, we describe the results and present an evaluation that compares the results with manually obtained groups.

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Paper citation in several formats:
Mykowiecka, A. and Marciniak, M. (2012). Clustering of Medical Terms based on Morpho-syntactic Features. In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (IC3K 2012) - KEOD; ISBN 978-989-8565-30-3; ISSN 2184-3228, SciTePress, pages 214-219. DOI: 10.5220/0004137502140219

@conference{keod12,
author={Agnieszka Mykowiecka. and Malgorzata Marciniak.},
title={Clustering of Medical Terms based on Morpho-syntactic Features},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development (IC3K 2012) - KEOD},
year={2012},
pages={214-219},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004137502140219},
isbn={978-989-8565-30-3},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development (IC3K 2012) - KEOD
TI - Clustering of Medical Terms based on Morpho-syntactic Features
SN - 978-989-8565-30-3
IS - 2184-3228
AU - Mykowiecka, A.
AU - Marciniak, M.
PY - 2012
SP - 214
EP - 219
DO - 10.5220/0004137502140219
PB - SciTePress