Ontology-based quantitative similarity metric for event matching in publish/subscribe system

被引：10

作者：

Kim, Hongjae ^{[1
]}

Kang, Sanggil ^{[2
]}

Oh, Sangyoon ^{[1
]}

机构：

[1] Ajou Univ, Dept Comp Engn, Suwon 443749, Gyeonggi, South Korea

[2] Inha Univ, Dept Comp & Informat Engn, Inchon 402751, South Korea

来源：

NEUROCOMPUTING | 2015年 / 152卷

关键词：

Event matching; Ontology; Publish/subscribe system; Quantitative similarity metric; Semantic ambiguity; SEMANTIC SIMILARITY;

D O I：

10.1016/j.neucom.2014.11.017

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Naval ships can achieve information superiority using publish/subscribe systems that integrate heterogeneous applications. The performance of publish/Subscribe communication systems depends on the effectiveness of the event matching between events and subscribers. Semantic Web technologies, including ontology, provide a platform and tools for event matching in publish/subscribe systems. Since semantic ambiguity exists in the ontologies, however, matching performance is not ideal. To improve event matching performance, we propose an ontology-based quantitative similarity metric where the frequency of keywords is used to measure the quantitative similarity. When compared to another ontology technique for semantic matching, the approximate semantic matching method, our evaluation results show a performance improvement in precision, recall, and F-measure. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：77 / 84

页数：8

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