USING NATURAL LANGUAGE PROCESSING FOR AUTOMATIC EXTRACTION OF ONTOLOGY INSTANCES

被引：0

作者：

Faria, Carla ^{[1
]}

Girardi, Rosario ^{[2
]}

Serra, Ivo ^{[2
]}

Macedo, Maria ^{[2
]}

Maranhao, Djefferson ^{[2
]}

机构：

[1] Fed Inst Educ Sci Technol Maranhao, Dept Comp Sci, Sao Luis, Maranhao, Brazil

[2] Univ Fed Maranhao, Dept Comp Sci, Sao Luis, Brazil

来源：

ICEIS 2010: PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS, VOL 2: ARTIFICIAL INTELLIGENCE AND DECISION SUPPORT SYSTEMS | 2010年

关键词：

Ontology; Ontology population; Natural language processing; Knowledge acquisition;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Ontologies are used by modern knowledge-based systems to represent and share knowledge about an application domain. Ontology population looks for identifying instances of concepts and relationships of an ontology. Manual population by domain experts and knowledge engineers is an expensive and time consuming task so, automatic and semi-automatic approaches are needed. This article proposes an initial approach for automatic ontology population from textual sources that use natural language processing and machine learning techniques. Some experiments using a family law corpus were conducted in order to evaluate it. Initial results are promising and indicate that our approach can extract instances with good effectiveness.

引用

页码：278 / 283

页数：6

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