Ecommerce Based Product Recommendation System

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creativework.keywordsMachine Learning, Ecommerce
dc.contributor.advisorDr. Shazzad Hosain
dc.contributor.authorMd. Mukith Al Alim
dc.contributor.authorMd. Ashiqur Rahman Ovi
dc.contributor.authorMd. Hasibul Hasan
dc.contributor.authorZeeshan Jamal
dc.contributor.id1711376042
dc.contributor.id1721444042
dc.contributor.id1722351642
dc.contributor.id1731699642
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2025-07-15
dc.date.accessioned2025-07-15T10:23:18Z
dc.date.available2025-07-15T10:23:18Z
dc.date.issued2021-11-30
dc.description.abstractThis paper represents a noble approach to develop a Machine Learning method like Ecommerce Based Product Recommendation System for developing country like Bangladesh. The product recommendation system is a filtering system that seeks to predict and show the items that a user would like to purchase. Recommender systems have become increasingly popular in recent years and utilized in various areas, including movies, news, books, research articles, search queries, social tags, and products in general. It is an essential feature of the digital world. Because users are often overwhelmed by choice and need help finding what they are looking for. If a recommender system is set up and configured properly, it can be the reason for a significant boost in revenues, satisfied customers, and more sales. In this project, we have employed several machine learning algorithms (NCF, SVD, Encoder-Decoder, KNN) to build a recommender system for products and also have developed a website through which users can geta list of recommendations of products based on their preferences. These algorithms’ performancesare evaluated on different metrics. KNN has been selected to deploy on the website among all the algorithms.
dc.description.degreeUndergraduate
dc.identifier.cd600000235
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/1273
dc.language.isoen_US
dc.publisherNorth-south University
dc.rights© NSU Library
dc.titleEcommerce Based Product Recommendation System
dc.typeProject
oaire.citation.endPage33
oaire.citation.startPage1
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