Shape-stabilized composite phase change film with good reversible thermochromic properties fabricated <i>via</i> phase inversion-assisted impregnation

Wang, Yuhan; Feng, Nianrong; Kang, Zhe; Wu, Dongfu

doi:10.1039/c9ra10255h

Cited by 9 publications

(1 citation statement)

References 42 publications

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“…In recent years, with the wave of big data, data-driven decision-making has been expanding and deepening in many industries, among which the film industry is very prominent [1][2][3][4][5][6][7][8][9][10]. After using machine learning technology to analyze many movie scoring data, the famous movie rental company Netflix can predict a user's scoring of a certain movie with a high degree of accuracy, and this indirectly becomes the core technology for recommending movies to users.…”

Section: Introductionmentioning

confidence: 99%

Research on English Movie Resource Information Mining Based on Dynamic Data Stream Classification

Duan

Gao

2021

Security and Communication Networks

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Massive English film and television resources will provide people with a rich content, while it has become more and more difficult for people to find the resources and information they need. Through the analysis of massive amounts of film and television data, the application system can effectively push the works that users may like. In response to this problem, we can build an English film and television resource information mining model by combining fuzzy neural network algorithms and dynamic data stream classification technology. Firstly, we use dynamic data stream classification technology to preprocess and screen English film and television resource information. Secondly, we use the fuzzy neural network algorithm to conduct data mining on related film and television resource information. The experimental results verify the superior performance of the English film and television resource information mining model established in this paper. This model can help people to find the resources and information they need.

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