Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 1


Published
on

July 15, 2022


Pages

1607-1616


DOI

Article

Construction of Intelligent Search Engine for Big Data Multimedia Resource Subjects Based on Partial Least Squares Structural Equation


Authors

Dan Huang Affiliation:
Beihai University of Art and Design, Beihai, China
, Dawei Zhang Affiliation:
Telecom Department, Beihai Vocational College, Beihai, Guangxi, 536000, China
and Rifat Hussain Affiliation:
College of Administrative Sciences, Applied Science University, Bahrain


Abstract

The equivalence of the research model is used as part of least squares to construct an intelligent search engine for large multimedia files. First of all, based on the intelligent design of big data analysis, optimize the search engine mode and create a good search environment. According to the research on big data technology, the application value of big data in intelligent search engine is analyzed, and a better search engine system is built on this basis. The basic theory of comparative modeling is also investigated. Then, on the big data management platform of Siping Fire Bureau, the operation of the big data search engine is identified according to the difference of evolutionary algorithms. Experiments show that the big data search engine, as part of the least squares structural equation algorithm, also improves user satisfaction, which is considered below. From the big data search engine, according to the difference of the evolutionary algorithm, the return time, return value and cost are improved, and the search itself can be effectively and accurately realized.


Keywords

Structural equation, Big data, smart, Search engine, Partial least squares, 34D30


Citation

Huang, D., Zhang, D., & Hussain, R. (2023). Construction of intelligent search engine for big data multimedia resource subjects based on partial least squares structural equation. Applied Mathematics and Nonlinear Sciences, 8(1), 1607–1616. https://doi.org/10.2478/amns.2022.2.0150

Published by: Engineering Journals

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