POPULATING BIOMEDICAL ONTOLOGIES FROM NATURAL LANGUAGE TEXTS

被引：0

作者：

Maria Ruiz-Martinez, Juana ^{[1
]}

Valencia-Garcia, Rafael ^{[1
]}

Martinez-Bejar, Rodrigo ^{[1
]}

Hoffmann, Achim ^{[2
]}

机构：

[1] Univ Murcia, Fac Comp Sci, Campus Espinardo, E-30100 Murcia, Spain

[2] Univ New South Wales, Sch Comp Sci & Engn, Sydney, NSW 2052, Australia

来源：

KEOD 2010: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON KNOWLEDGE ENGINEERING AND ONTOLOGY DEVELOPMENT | 2010年

关键词：

Ontology Population; Semantic Role; Knowledge Acquisition; KNOWLEDGE; RECOGNITION; ACQUISITION; EXTRACTION; MODEL;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Ontology population is a knowledge acquisition activity that relies on (semi-) automatic methods to transform unstructured, semi-structured and structured data sources into instance data. In this work, a semantic-role based process for ontology population is presented that provides a suitable framework for textual knowledge acquisition in the biological domain. In particular, with our approach, a given ontology can be enriched by adding instances gathered from biological natural language texts. Our system's modular architecture provides a greater versatility than current approaches in the mentioned domain, as the process of ontology population is not directly dependent on the linguistic rules developed from the corpus.

引用

页码：27 / 36

页数：10

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