Analysing the Role of AI-powered Recommender Systems in Enhancing Customer Engagement in Online Marketplaces: Developing A Product Recommendation System

Ozcelik, Erdal (2024) Analysing the Role of AI-powered Recommender Systems in Enhancing Customer Engagement in Online Marketplaces: Developing A Product Recommendation System. Masters thesis, Dublin, National College of Ireland.

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Abstract

The objective of this research project is to examine the influence of AI-driven recommender systems on customer engagement in online marketplaces. The primary focus lies on collaborative filtering methods and hybrid recommender systems, which seamlessly integrate collaborative filtering with natural language processing techniques. Utilizing the Amazon Sales Dataset sourced from Kaggle, the study endeavours to construct and analyse these recommendation systems. The project also conducts a survey to evaluate the effectiveness of these systems, using criteria such as relevance, diversity, satisfaction, and visual appeal. In addition to the technical aspects, delving into the broader implications of AI-powered Recommender Systems on customer engagement. This is achieved through a comprehensive review of related works and literature, exploring their functionality, principles, and impact on customer loyalty. Moreover, the research identifies the key factors contributing to the effectiveness of these systems while also addressing associated ethical issues. In essence, this project provides a comprehensive exploration of AI-driven recommender systems, their construction, evaluation, and broader implications within the context of online marketplaces.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Del Rosal, Victor UNSPECIFIED
Uncontrolled Keywords:	AI-powered recommender systems; Collaborative filtering; Natural language processing (NLP); Customer engagement; Online marketplaces; Personalised recommendations
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 P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing H Social Sciences > HF Commerce > Electronic Commerce
Divisions:	School of Computing > Master of Science in Artificial Intelligence for Business
Depositing User:	Tamara Malone
Date Deposited:	07 Apr 2025 12:09
Last Modified:	07 Apr 2025 12:09
URI:	https://norma.ncirl.ie/id/eprint/7384

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