Building Domain Ontologies Out of Folksonomies and Linked Data

被引：4

作者：

Garcia-Silva, Andres ^{[1
]}

Jael Garcia-Castro, Leyla ^{[2
]}

Garcia, Alexander ^{[3
]}

Corcho, Oscar ^{[1
]}

机构：

[1] Univ Politecn Madrid, Ontol Engn Grp, Boadilla Del Monte 28660, Spain

[2] Univ Jaume 1, Dept Comp Languages & Syst, Castellon de La Plana 12071, Spain

[3] Linking Data IO LLC, Ft Collins, CO 80524 USA

来源：

INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS | 2015年 / 24卷 / 02期

关键词：

Ontology learning; knowledge acquisition; linked data; folksonomy;

D O I：

10.1142/S021821301540014X

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we propose an automatic method for building domain ontologies where we leverage the emerging vocabulary from social tagging systems, and the existing semantics in the Linked Open Data cloud to enrich semantically the terms that shape the domain ontology. We systematically capture a domain vocabulary by searching for relevant resources in the folksonomy graph using a spreading activation strategy. We use the vocabulary to identify domain classes and relationships among them by querying knowledge bases published as linked data. We present a case study in the financial domain where we experiment with different settings and show the feasibility of our approach using real folksonomy data.

引用

页数：22

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