English Translation Template Retrieval Based on Semantic Distance Ontology Knowledge Recognition Algorithm

Abstract

With the rapid development of the Internet, data information has begun to spread rapidly on the Internet, and the types and fields involved are becoming more and more diverse. With the deepening of internationalization, English information has also become a common entry for tourism. Relatively speaking, the translation of English documents is also on the agenda. The intricate literature information has put forward a more specialized and vertical demand for retrieval. Traditional retrieval systems usually use string matching algorithms to search, but this technology cannot perform semantic expansion of query conditions. In the case of “multiple words with one meaning” and “polysemy of one word,” the retrieval accuracy of traditional retrieval systems decreases. In order to solve the previously mentioned problems, this study proposes semantic retrieval based on domain ontology technology. The purpose of semantic retrieval is to semantically expand the user’s query conditions on the basis of accurately understanding the retrieval conditions. At the same time, with the help of the constructed domain ontology, it provides more accurate and comprehensive retrieval services for document retrieval. The experimental results of this study show that, for the clustering of the entire dataset, the number of ontology concepts in each article is 61% of that, before merging, which effectively reduces the complexity of the semantic network model. Therefore, the validity of the ontology concept merging algorithm proposed in this study is verified.