Upgrading Traditional E-Commerce Systems with A Knowledge- Based Recommendation System

Siljanoska, Teodora and Blazeska Tabakovska, Natasha (2024) Upgrading Traditional E-Commerce Systems with A Knowledge- Based Recommendation System. In: 14th International Conference on Applied Internet and Information Technologies AIIT 2024, 8 November, 2024, Zrenjanin, Serbia.

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Abstract

In today’s e-commerce, there is a need for intelligent recommendation systems to help consumers choose products. This paper presents an upgrade to traditional e-commerce systems by implementing a knowledge-based recommendation system. The focus is on collaborative filtering, which uses data on consumer preferences to provide personalized product suggestions. A user-user collaborative filtering algorithm is applied, which groups users according to similarities in their choices and suggests products that are popular among consumers with similar preferences.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Scientific Fields (Frascati) > Engineering and Technology > Electrical engineering, electronic engineering,information engineering
Divisions:	Faculty of Information and Communication Technologies
Depositing User:	Mrs Natasha Blazheska-Tabakovska
Date Deposited:	16 Dec 2024 07:39
Last Modified:	16 Dec 2024 07:39
URI:	https://eprints.uklo.edu.mk/id/eprint/10541

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