Excel International Journal of Technology, Engineering & Management

ISSN : (Print): 2348–0378 |
(Online): 2349–8455

2.5

CiteScore

8.8

Global Impact Factor

RECOMMENDATION FOR E-COMMERCE USING MACHINELEARNING ALGORITHMS

Paper ID: EIJTEM_2023_10_2_18-24

Author's Name: D. Himagiri , Prateek Bhure , Sundaram , Rebbavarapu Vinithasree and Bobbili Shyam

Volume: 10

Issue: 2

Year: 2023

Page No: 18-24

Abstract:

One of the possible frustrations that many electronic-commerce platform users face is information overload. When using an online store to make a purchasing decision, Now a days it s very difficult for internet user to select their media and choice of interest. To address this issue, recommender systems are widely used. Recommender systems assist users in locating the productsthey seek by efficiently filtering, prioritising, and generating relevant information. By producing targeted and pertinent material, recommendation systems aim to reduce the time and effort required for Internet searches, speed up online transactions, and satisfy users of online shopping platforms.The paper presents about the product recommendations on ecommerce based on user preferences

Keywords: Recommendation system, filtering, e-commerce, machine learning

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