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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.
| Autorius: | Suhas G. K., Piyush Kumar Pareek, Priya Nandihal, |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2022 |
| Knygos puslapių skaičius: | 116 |
| ISBN-10: | 6139459338 |
| ISBN-13: | 9786139459339 |
| Formatas: | 220 x 150 x 7 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Recommendation Based Interaction: Recommendation Based Interactivity through Multiple Platforms in Big Data“
