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Social and Location Analysis for Similarity Assessment: Multiparameter Social Search Based on Social Preferences and User Movements

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  • Albert Asmaryan

    (Bauman Moscow State Technical University, Moscow, Russia)

  • Alexey Levanov

    (Bauman Moscow State Technical University, Moscow, Russia)

  • Irina Borovik

    (Bauman Moscow State Technical University, Moscow, Russia)

Abstract

This article introduces the method to assess similarity based on Facebook Graph API and users' movements. All movements of users are collected and analyzed. This paper presents a two-step multiparameter algorithm that generates recommendations based on users' 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. The given result can be used and applied in various spheres of our lives to identify different relationships between people.

Suggested Citation

  • Albert Asmaryan & Alexey Levanov & Irina Borovik, 2016. "Social and Location Analysis for Similarity Assessment: Multiparameter Social Search Based on Social Preferences and User Movements," International Journal of Interdisciplinary Telecommunications and Networking (IJITN), IGI Global, vol. 8(4), pages 22-33, October.
    • Handle: RePEc:igg:jitn00:v:8:y:2016:i:4:p:22-33
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