Top- N recommendation algorithm integrated neural network
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S.I. : SPIOT 2020
Top-N recommendation algorithm integrated neural network Liang Zhang1 • Liang Zhang2 Received: 21 July 2020 / Accepted: 14 October 2020 Ó Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract With the gradual popularization of social informatization, people’s information security is gradually threatened. The development of the Internet has gradually exposed people’s privacy, and the protection of the privacy of people in the era of Internet information has become a topic of concern to all people. This research mainly discusses the research of the TopN recommendation algorithm with integrated neural network. The purpose of protecting people’s privacy is achieved by interfering with the Top-N recommendation algorithm on the Internet signal. In response to people’s concerns, the TopN recommendation algorithm with integrated neural network was used during the experiment. The experimenters were randomly selected from netizens who frequently used computers to measure the privacy and security of each group of researchers and the signal of the Top-N recommendation algorithm. Interference level. The use of the Top-N recommendation algorithm is divided into six levels, and the experimentally measured information protection rate is 88% when the use level of the Top-N recommendation algorithm is F level. In the case of signal interference, the interference intensity is divided into five levels. Similarly, when the signal interference intensity is 5, the information leakage rate is at least 10%. The selection of personnel throughout the experiment is random and the interference during the experiment and the use of the Top-N recommendation algorithm with integrated neural network are divided according to levels. The research results show that when the signal interference intensity is 5 and the recommended algorithm is F, the privacy protection of netizens is the best. The Top-N recommendation algorithm with integrated neural network has important potential value in protecting people’s privacy. Keywords Integrated neural network Top-N recommendation algorithm Signal interference Privacy rate
1 Introduction 1.1 Background and significance The development of computers has promoted rapid changes in many fields, and the disclosure of privacy has also caused problems for Internet enthusiasts. When a user uses a computer to search for related vocabulary, the computer will record the user’s search vocabulary by default, and the
& Liang Zhang [email protected] Liang Zhang [email protected] 1
School of Economics and Management, Guizhou Normal University, Guiyang 550001, China
2
School of Aerospace Engineering, Tsinghua University, Beijing 100084, China
relevant criminals will steal the user’s information based on this weakness. The research of the Top-N recommendation algorithm with integrated neural network in user privacy can be said to be very novel. When a computer user searches for information, the Top-N recommendation algorithm with inte
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