Content-Based Recommender System for Online Stores Using Expert System
Bogdan Walek, Petra Spackova · 2018
This paper deals with a content-based recommender system for online stores using the expert system. We propose an algorithm which adapts the content based on user preferences and the content viewed by the user. The main goal of the recommender system is to propose and deliver suitable content to the user. One of the goals of the proposed recommender system is to decrease the cold start effect. At the end of the paper, the proposed system is experimentally verified.