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A Cognitive Assistant Functional Model and Architecture for the Social Media Victim Behavior Prevention

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Artificial Intelligence Methods in Intelligent Algorithms (CSOC 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 985))

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Abstract

Nowadays the facilities of a parental control are not sufficient due to the numerous mobile devices and Internet access points. Another approach to control the children’s behavior in the Social Media is to augment the human capabilities by the usage of a cognitive assistant. Cognitive assistants usually provide such features as self-learning, adaptive behavior, big data processing, etc. This paper focuses on the design of the cognitive assistant based on the authorship attribution methods. The major functions of the cognitive assistant as an online service are highlighted, the authorship attribution methods are analyzed and the base model and architecture of the cognitive assistant service are presented. The cognitive map usage as a data analysis intelligent technique is proposed. Also some issues of the service (i.e. scalability, dependability, integration) are considered and discussed.

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Acknowledgement

The paper has been prepared within the RFBR project 18-29-22093.

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Authors and Affiliations

  1. Southern Scientific Center of the Russian Academy of Science, 41 Chekhov Street, Rostov-on-Don, 344006, Russia

    Eduard Melnik

  2. Southern Federal University, Rosdtov-on-Don, Russia

    Iakov Korovin

  3. Scientific Research Institute of Multiprocessor Computer Systems of Southern Federal University, 2 Chekhov Street, GSP-284, Taganrog, 347928, Russia

    Anna Klimenko

Authors
  1. Eduard Melnik
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  2. Iakov Korovin
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  3. Anna Klimenko
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Corresponding author

Correspondence to Anna Klimenko .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in ZlĂ­n, ZlĂ­n, Czech Republic

    Radek Silhavy

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Melnik, E., Korovin, I., Klimenko, A. (2019). A Cognitive Assistant Functional Model and Architecture for the Social Media Victim Behavior Prevention. In: Silhavy, R. (eds) Artificial Intelligence Methods in Intelligent Algorithms. CSOC 2019. Advances in Intelligent Systems and Computing, vol 985. Springer, Cham. https://doi.org/10.1007/978-3-030-19810-7_6

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