The expansion of image information using ontologies to enhancing the efficiency of data retrieval tasks

This paper explores the enhancement of image information descriptions using ontologies to improve the efficiency of data retrieval tasks. Initially, the paper reviews current methods of describing image information in databases, private servers, and web documents. Based on this review, we propose an improved approach that provides more accurate and detailed descrip￾tions. Our proposed method involves the use of a custom-designed ontology specifically created to semantically describe image information in web documents. This ontology enables a richer and more nuanced representation of image data, facilitating better understanding and retrieval. The proposed approach aims to significantly enhance the accuracy and efficiency of data retrieval in both databases and web search engines. And for that reason, at the end of the article, we described our application for verifying ontology deployment in a simple parser. After deploying the ontology, we found that after extracting the images from the web page, we got a much more accurate description of the animal than what was provided to us from the web document. The success of our parser in determining the more detailed description depended on the sample used of randomly selected web documents and the data extraction success rate was 88%, with 72% of outputs being correctly filtered. In addition, animal identification success was observed be up to 90%.