A novel algorithm for ontology matching

Author:

Akbari Ismail1,Fathian Mohammad2

Affiliation:

1. Industrial Engineering Department, Iran University of Science and Technology, Tehran, Iran,

2. Industrial Engineering Department, Iran University of Science and Technology, Tehran, Iran

Abstract

Ontology matching is an essential aspect of the Semantic Web with a goal of finding alignments among the entities of given ontologies. Ontology matching is a necessary step for establishing interoperation and knowledge sharing among Semantic Web applications. In this study we present an algorithm and a tool developed based on this algorithm to find correspondences among entities of input ontologies. The proposed algorithm uses a new lexical similarity measure and also utilizes structural information of ontologies to determine their corresponding entities. The lexical similarity measure generates a bag of words for each entity based on its label and description information. The structural approach creates a grid for each node in the ontologies. The combination of lexical and structural approaches creates the similarity matrix between the source and target ontologies. The proposed algorithm was tested on a well known benchmark and also compared to other algorithms presented in the literature. Our experimental results show the proposed algorithm is effective and outperforms other algorithms.

Publisher

SAGE Publications

Subject

Library and Information Sciences,Information Systems

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A multi‐objective particle swarm optimization for matching domain ontologies;Internet Technology Letters;2023-01-05

2. Natural ontologies with elastic matching for elicited knowledge comparison;Journal of Intelligent & Fuzzy Systems;2020-08-31

3. Instance-Based Ontology Matching: A Literature Review;Advances in Intelligent Systems and Computing;2018

4. Ontology representation and mapping of common fuzzy knowledge;Neurocomputing;2016-11

5. Approximate pattern matching with gap constraints;Journal of Information Science;2016-07-10

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