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Method for Extracting Information of Database of Smart Phone Terminal in Lock Screen Mode

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Multimedia Technology and Enhanced Learning (ICMTEL 2020)

Abstract

In order to improve the database management and scheduling ability of smartphone terminal, it is necessary to optimize the information extraction of smartphone terminal database in lock screen mode. through the dynamic mining of smartphone terminal database data, the optimal processing of smart phone terminal database data information is realized, and this paper proposes an algorithm to extract the resource information of the smartphone terminal database under the lock screen mode based on the Internet. Using distributed wireless sensor to form the Internet model of smart phone database collection, and the optimal deployment design of data acquisition Internet of things node is carried out. The spectrum analysis method is used to detect the abnormal resource information of smart phone terminal database in lock screen mode, and the detection results are fuzzy clustering to realize the extraction of smart phone terminal database resource information in locked screen mode under the environment of Internet of things. The simulation results show that the algorithm has high accuracy, good recall, strong anti-interference ability and good adaptive ability to collect the resource information of smart phone terminal database in lock screen mode.

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Correspondence to Juan Du .

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Du, J., Xie, R. (2020). Method for Extracting Information of Database of Smart Phone Terminal in Lock Screen Mode. In: Zhang, YD., Wang, SH., Liu, S. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-030-51100-5_3

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  • DOI: https://doi.org/10.1007/978-3-030-51100-5_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-51099-2

  • Online ISBN: 978-3-030-51100-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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