Subjective Evaluation of Recommender System Using Modified Delone &Mclean Success Model

Abstract

One of the most significant and difficult challenges of recommender systems is recommending items that satisfy user needs and thus improve the quality of the experience in the system. In the context of recommender systems, collaborative filtering (CF) is one of the most widely used techniques. A modified and updated version of Delone and McLean IS success factor model was used to assess how
recommender systems were perceived. The IS success model was changed using the privacy variable. Information quality, service quality, system quality, and privacy are the variables considered in this study. These analyses used multiple linear regression to determine how those variables affected the user. The study's findings indicate that while information quality has little bearing on recommender creation, privacy, service quality, and system quality do. This encourages users to return to the website, which boosts sales and profitability