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Research of Multichannel User Data to Identify the Degree of Similarity: Multiparameter Social Search Based on Social Preferences and User Movements

Research of Multichannel User Data to Identify the Degree of Similarity: Multiparameter Social Search Based on Social Preferences and User Movements
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Author(s): Albert Asmaryan (Bauman Moscow State Technical University, Russia), Alexey Levanov (Bauman Moscow State Technical University, Russia)and Irina Borovik (Bauman Moscow State Technical University, Russia)
Copyright: 2019
Pages: 17
Source title: Strategic Innovations and Interdisciplinary Perspectives in Telecommunications and Networking
Source Author(s)/Editor(s): Natarajan Meghanathan (Jackson State University, USA)
DOI: 10.4018/978-1-5225-8188-8.ch002

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Abstract

This chapter introduces the method to assess similarity based on Facebook Graph API and user movements. All movements of users are collected and analyzed. The chapter presents an additional method for analyzing user-generated images on Instagram Graph API. The chapter presents a two-step multiparameter algorithm that generates recommendations based on user social activity and movements. A flexible mechanism for the calculations of time that one spends on a variety of social activities to more accurately identify the relationships between users is presented. To reduce the load on the application, the algorithms of data analysis and transfer optimization are proposed. The ultimate result of the study is to build a platform based on the “client-server” model and includes a mobile app on the iOS platform and server, which would be set up on the “LAMP” platform (L - Linux operating system, A - Apache web server, M - MySQL database, P - PHP programming language). The given result can be used and applied in various spheres of our lives to identify different relationships between people.

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