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Design of Intelligent Response System for Business English (Training) Based on Improved GLR Algorithm

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Application of Intelligent Systems in Multi-modal Information Analytics (ICMMIA 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 136))

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Abstract

With the development of the Internet and e-commerce, massive amounts of data and information exist on the Internet, and valuable information is usually hidden behind complex and diverse data. For companies, it is very important to be able to analyze these data comprehensively, accurately and intelligently, and to dig out effective information from them to formulate personalized product marketing strategies for the company, so as to gain an advantage in the fierce market competition. Business intelligence is an important part of enterprise informatization, and it is a series of methods, technologies and software used to improve the performance of enterprise operations. It applies advanced information technology to the entire enterprise, through the application of data warehouse technology, data mining technology, information visualization technology and other information analysis and mining, can promote the better development of enterprise sales. Therefore, the application of business intelligence theory in the analysis of competing products can truly provide accurate, intelligent, and credible data services for corporate decision-making. Starting from the actual needs of an enterprise, this paper designs an intelligent response system for business English (training) based on the improved GLR algorithm. In the system reliability test, the data reliability of all modules is above 0.8, which improves the efficiency of business English training.

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Correspondence to Ying Lian .

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Lian, Y. (2022). Design of Intelligent Response System for Business English (Training) Based on Improved GLR Algorithm. In: Sugumaran, V., Sreedevi, A.G., Xu, Z. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. ICMMIA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 136. Springer, Cham. https://doi.org/10.1007/978-3-031-05237-8_2

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