Recommendation Based Interaction

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Details

A forum that encompasses the interconnectedness of services and social media channels is developed. By allowing users to model interest-based relevant sources in Big Data, it highlights user value and bridges user needs across social media and technical content.The proposed approach built on previous user-centric Big Data implementations, which were primarily aimed at strengthening internal services through multiplatform information access and fluid content sharing. This research is focused on an interest-based architecture that allows radio listeners to navigate professional and social media information sources. The adaptive Big Data User-centric model took advantage of a versatile world that was responsive to evolving data fluxes between social networking site services.

Autorentext

Dr.Suhas G KShridevi Institute of Engineering and Technology,TumkurDr. Piyush Kumar Pareek, Dept. of Computer Science & Engineering,Nitte Meenakshi Institute of Technology, Yelahanka, Bengaluru Dr.Priya Nandihal Dayananda Sagar Academy of Technology and Management.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09786139459339
    • Anzahl Seiten 116
    • Genre IT Encyclopedias
    • Herausgeber LAP LAMBERT Academic Publishing
    • Gewicht 191g
    • Untertitel Recommendation Based Interactivity through Multiple Platforms in Big Data
    • Größe H220mm x B150mm x T7mm
    • Jahr 2022
    • EAN 9786139459339
    • Format Kartonierter Einband
    • ISBN 6139459338
    • Veröffentlichung 22.03.2022
    • Titel Recommendation Based Interaction
    • Autor Suhas G. K. , Piyush Kumar Pareek , Priya Nandihal
    • Sprache Englisch

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