Cost Preference Product Service using Recommendation System

In today's vast and diverse e-commerce landscape, consumers often face the challenge of navigating multiple platforms to find the best deals on specific products. The need to search through various websites and apps for a particular item from a preferred brand within a defined price range can b...

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Bibliographic Details
Published in:	2023 3rd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA) pp. 1049 - 1055
Main Authors:	Reddy, A.Siva Krishna, Reddy, S.Ruchitha, Sathish, Jadhav, Ravikumar, Ade, Rahil, Mohammad, Adithya, Suddala
Format:	Conference Proceeding
Language:	English
Published:	IEEE 21-12-2023
Subjects:	Costs E-commerce landscape Efficient implementation Electronic commerce Faces Financial constraints Hassle-free Industry applications Navigation Personalized suggestions Recommendation system Recommender systems User experience User preferences
Online Access:	Get full text
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Summary:	In today's vast and diverse e-commerce landscape, consumers often face the challenge of navigating multiple platforms to find the best deals on specific products. The need to search through various websites and apps for a particular item from a preferred brand within a defined price range can be time-consuming and overwhelming. To streamline this process and enhance the shopping experience for users, the implementation of an efficient recommendation system is pivotal. The primary goal of this research work is to develop a robust recommendation system that offers personalized suggestions to users based on their preferences and financial constraints. This system aims to alleviate the hassle of sifting through multiple platforms by providing tailored recommendations, taking into account factors such as product categories, sub-categories, brand preferences, and price ranges.
DOI:	10.1109/ICIMIA60377.2023.10426235