Sensor Ontology Metamatching with Heterogeneity Measures

Joint Authors

Xue, Xingsi
Lu, Jiawei
Jiang, Chengcai
Huang, Yikun

Source

Wireless Communications and Mobile Computing

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-11-25

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Information Technology and Computer Science

Abstract EN

The heterogeneity problem among different sensor ontologies hinders the interaction of information.

Ontology matching is an effective method to address this problem by determining the heterogeneous concept pairs.

In the matching process, the similarity measure serves as the kernel technique, which calculates the similarity value of two concepts.

Since none of the similarity measures can ensure its effectiveness in any context, usually, several measures are combined together to enhance the result’s confidence.

How to find suitable aggregating weights for various similarity measures, i.e., ontology metamatching problem, is an open challenge.

This paper proposes a novel ontology metamatching approach to improve the sensor ontology alignment’s quality, which utilizes the heterogeneity features on two ontologies to tune the aggregating weight set.

In particular, three ontology heterogeneity measures are firstly proposed to, respectively, evaluate the heterogeneity values in terms of syntax, linguistics, and structure, and then, a semiautomatically learning approach is presented to construct the conversion functions that map any two ontologies’ heterogeneity values to the weights for aggregating the similarity measures.

To the best of our knowledge, this is the first time that heterogeneity features are proposed and used to solve the sensor ontology metamatching problem.

The effectiveness of the proposal is verified by comparing with using state-of-the-art ontology matching techniques on Ontology Alignment Evaluation Initiative (OAEI)’s testing cases and two pairs of real sensor ontologies.

American Psychological Association (APA)

Xue, Xingsi& Lu, Jiawei& Jiang, Chengcai& Huang, Yikun. 2020. Sensor Ontology Metamatching with Heterogeneity Measures. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1214476

Modern Language Association (MLA)

Xue, Xingsi…[et al.]. Sensor Ontology Metamatching with Heterogeneity Measures. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1214476

American Medical Association (AMA)

Xue, Xingsi& Lu, Jiawei& Jiang, Chengcai& Huang, Yikun. Sensor Ontology Metamatching with Heterogeneity Measures. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1214476

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1214476