AN APPROACH FOR IMPLEMENTING A MULTIDIMENSIONAL RECOMMENDATION SYSTEM FOR ONLINE RETAIL SERVICES OR PORTALS

Prof. Nalini A. Mhetre, Meghraj Falle, Praveen Shukla, Saurabh Chaudhari, Aditya Sawant

Abstract


A newly proposed algorithmic approach that can be deployedin the  implementation of recommendation system which can be used at the  clientas well as server end. PID is a closed loop, self-tuning algorithm which ispredominantly implemented in mechatronics instruments where manual supervision is not feasible and it functions for corrections of errors quantifiablein physical measures. In this approach, we propose a similar outlook to analgorithm for implementation of recommendation system. There exist nophysical errors in computer based systems as such but we can abstractlymap this error to irrelevancy. If we were to map errors in physical dimensions to irrelevancy in computer systems it can be approximately stated tobe higher the error, higher the irrelevancy. Also, the availability of multiplefactor assessment in PID algorithms can be used to add multidimensionalapproach in implementation. As proposed and analysed the implementationis expected to provide with faster as well as large data compliant analyticsoption.

Keywords


Data mining,Multidimensional recommendation system,Performance Analysis,PID algorithm,Product Equivalence Value,Self-Tuning

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References


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