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Information Seminar Paper

Title

Improving Lexical Matching in Ontology Alignment by Considering the Importance of Grammatical Position of Words

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Abstract

 Considering the need for knowledge sharing in various Semantic web domains, the concept of Ontology has been introduced as a method for standardizing information. However, for collaboration between different knowledge domains, the need for Alignment between ontologies has arisen. Ontology Alignment refers to the process of mapping pairs of entities between two ontologies. The most important component for finding aligned pairs of entities between two ontologies is the use of Similarity measures. Similarity measures encompass three categories: semantic, lexical, and structural similarities. Some Alignment methods use a single measure, while more advanced approaches like AML and LOGMAP combine multiple Similarity measures to achieve better results. In this article, we have been able to improve the AML method by emphasizing the importance of the grammatical position of words in the textual content of entities, and enhance its performance to 94% in terms of the F-measure in the anatomy Ontology dataset.

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    APA: Copy

    Mokhtari, Shakila, & Ghanbarpour, Asieh. (2024). Improving Lexical Matching in Ontology Alignment by Considering the Importance of Grammatical Position of Words. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/1147655/en

    Vancouver: Copy

    Mokhtari Shakila, Ghanbarpour Asieh. Improving Lexical Matching in Ontology Alignment by Considering the Importance of Grammatical Position of Words. 2024. Available from: https://sid.ir/paper/1147655/en

    IEEE: Copy

    Shakila Mokhtari, and Asieh Ghanbarpour, “Improving Lexical Matching in Ontology Alignment by Considering the Importance of Grammatical Position of Words,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2024, [Online]. Available: https://sid.ir/paper/1147655/en

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