Solving Ontology Meta-Matching Problem Through an Evolutionary Algorithm With Approximate Evaluation Indicators and Adaptive Selection Pressure

Ontology applies commonly to solve the problem of heterogeneity of data in the Semantic Web, but the heterogeneity problem between two ontologies seriously affects their communication. As an effective method, ontology matching can address the problem above, whose core technique is the similarity mea...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE access Vol. 9; pp. 3046 - 3064
Main Authors:	Lv, Qing, Jiang, Chengcai, Li, He
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptive algorithms adaptive selection pressure Alignment approximate evaluation indicator Convergence Evaluation evolution algorithm Evolutionary algorithms Genetic algorithms Heterogeneity Indicators Knowledge representation Linguistics Matching Ontologies Ontology Ontology meta-matching Power engineering Semantic web Similarity similarity measure Similarity measures Syntactics Weight measurement
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!