MULTIPLE KERNEL LEARNING FOR ONTOLOGY INSTANCE MATCHING

被引：0

作者：

Ardila, Diego ^{[1
]}

Abasolo, Jos ^{[1
]}

Lozano, Fernando ^{[1
]}

机构：

[1] Univ Los Andes, Bogota, Colombia

来源：

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

关键词：

Ontology instance matching; Similarity measure combination; Multiple kernel learning; Indefinite kernels;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper proposes to apply Multiple Kernel Learning and Indefinite Kernels (IK) to combine and tune Similarity Measures within the context of Ontology Instance Matching. We explain why MKL can be used in parameter selection and similarity measure combination; argue that IK theory is required in order to use MKL within this context; propose a configuration that makes use of both concepts; and present, using the IIMB bechmark, results of a prototype to show the feasibility of this idea in comparison with other matching tools.

引用

页码：311 / 318

页数：8

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