Title: Survey on personalised recommendation system development in big data analytics

Authors: T.P. Ezhilarasi; K. Sashi Rekha

Addresses: Department of CSE, Saveetha School of Engineering, SIMATS, Chennai, India ' Department of CSE, Saveetha School of Engineering, SIMATS, Chennai, India

Abstract: In recent times, recommendation systems (RSs) are extensively used by diverse companies to raise offerings and profits with the target of providing specialised services to users. To meet the needs of the project, the objective is to provide a good idea of the RS in place for the support. To achieve this objective, this work provides a systematic survey of a personalised RS (PRS) based on the agricultural context for analysing the data. The results demonstrate that a combination of recommendations and data analysis is not extremely used for general practices. However, validation is regarded as infrequent in agriculture. From the investigator's perspective, this review provides for an in-depth analysis of learning approaches and data analysis based on the preliminary need for agriculture needs. This leads to an extremely complex solution for identifying an effective solution that assists real agriculture for earlier predictions. Therefore, in this work, the author suggests the use of data analysis and PRS to facilitate implementation in various areas.

Keywords: personalised recommendation systems development; agriculture; big data analytics; BDA; systematic reviews; the optimal solution.

DOI: 10.1504/IJESMS.2022.123950

International Journal of Engineering Systems Modelling and Simulation, 2022 Vol.13 No.3, pp.194 - 199

Received: 12 Jun 2021
Accepted: 16 Aug 2021
Published online: 05 Jul 2022 *

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