Semantic similarity algorithm of geo-ontology concept based on BP neural network

Qianwen Yao; Nina Meng

doi:10.1117/12.2635411

12 May 2022 Semantic similarity algorithm of geo-ontology concept based on BP neural network

Qianwen Yao, Nina Meng

Proceedings Volume 12173, International Conference on Optics and Machine Vision (ICOMV 2022); 121731V (2022) https://doi.org/10.1117/12.2635411
Event: International Conference on Optics and Machine Vision (ICOMV 2022), 2022, Guangzhou, China

Abstract

Aiming at the problems of single considerations, poor universality, and strong subjectivity in the semantic similarity calculation method for the geographic information field, combined with the structural characteristics of the geo-ontology, an algorithm for semantic similarity of geo-ontology concept based on BP neural network is proposed. Based on the traditional calculation of semantic distance and information factor based on the ontology hierarchical tree structure, the ontology properties value and semantic relationship between geographical concepts are extracted based on the authoritative concept description in the field, and they are transformed into the expression of semantic similarity. Synthesize the influence of four types of factors on semantic similarity, and use BP neural network to optimize the weight. Calculating the correlation coefficient between this algorithm and the expert evaluation results and comparing it with other algorithms shows that this method can effectively improve the accuracy and effectiveness of the semantic similarity calculation of geographic information concepts.

Citation Download Citation

Qianwen Yao and Nina Meng "Semantic similarity algorithm of geo-ontology concept based on BP neural network", Proc. SPIE 12173, International Conference on Optics and Machine Vision (ICOMV 2022), 121731V (12 May 2022); https://doi.org/10.1117/12.2635411

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