Optimizing Personalization in E-commerce Platforms using Artificial Intelligence and Machine Learning Techniques

Bayram, Alper (2024) Optimizing Personalization in E-commerce Platforms using Artificial Intelligence and Machine Learning Techniques. Masters thesis, Dublin, National College of Ireland.

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Abstract

Modern technology relies heavily on Machine Learning to address practical problems. Similarly, it is extensively utilized in the e-commerce business to create a range of recommendation systems. The beauty items sold on Amazon and the Home Depot Product Search Relevance dataset are the subject of this proposal, which aims to improve e-personalization commerce’s. The suggested approach utilizes ML approaches to combine contextual personalization with AI-powered chatbots. Improved accuracy and contextual relevance in user suggestions is the goal of the proposed approach, which seeks to overcome the shortcomings of existing methods like Collaborative Filtering and Content-Based Recommendation.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Sahni, Anu UNSPECIFIED
Uncontrolled Keywords:	E-commerce; personalization; artificial intelligence; SVD algorithm; Hyperparameter tuning; NMF algorithm; KNNBaseline algorithm
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence H Social Sciences > HF Commerce > Electronic Commerce Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	05 Jun 2025 14:07
Last Modified:	05 Jun 2025 14:07
URI:	https://norma.ncirl.ie/id/eprint/7764

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