Research on Semantic Information Retrieval Based on Improved Fish Swarm Algorithm

Authors

DOI:

https://doi.org/10.13052/jwe1540-9589.21313

Keywords:

semantic information retrieval; improved fish swarm algorithm, classification accuracy

Abstract

In order to improve the effectiveness of semantic information retrieval, the improved fish swarm algorithm is proposed to carry out semantic information retrieval. Firstly, the system of semantic information retrieval is designed, and theory model of search engine is established. Secondly, the information retrieval model based on semantic similarity is constructed, and the mathematical model is deduced. Thirdly, the improved fish algorithm is established, and the analysis procedure of it is designed. Finally, the simulation analysis of semantic information retrieval is carried out, results show that the proposed model can obtain higher classification accuracy, precision rare and recall rate, therefore it has higher performance on semantic information retrieval.

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Author Biography

Ming Hu, Wuhu Institute of Technology, China

Hu Ming, Master of Engineering, associate professor of Wuhu Institute of Technology, member of the national curriculum ideological and political team. He has won the first prize of The Teachers’ Teaching Ability Competition of Anhui Province, the Gold Medal of “Internet ++” Innovation and Entrepreneurship Competition, the first prize of the Teaching Achievement Award of Anhui Province for 3 times. He patended 7 inventions. He has taken many teaching and research projects such as “Research on domain name detection, classification and clustering algorithm based on deep learning”, “Research and practice of effective operation management based on online teaching Quality improvement” and so on.

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Published

2022-03-22

How to Cite

Hu, M. . (2022). Research on Semantic Information Retrieval Based on Improved Fish Swarm Algorithm. Journal of Web Engineering, 21(03), 845–860. https://doi.org/10.13052/jwe1540-9589.21313

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Articles