{"id":105,"name":"Nguyen","url":"","description":"I'm Winnie Nguyen, a senior majoring in Computer Science and Quantitative Economics at Earlham College.\r\nAbout my CS Capstone Project:\r\nIn recent years, the need for recommender systems as a tool to improve user interaction, provide personalized services, and enrich shopping potential to raise revenue has been increasing along with the sharp expansion of online shopping platforms. However, with the overload of huge amounts of customer data, recommender systems face challenges in processing data robustly and accurately. In this paper, I am using a matrix factorization technique called singular value decomposition (SVD) in item-based collaborative filtering. Despite the ability to quickly produce high-quality recommendations, SVD has expensive matrix factorization steps - scalability matters that need an updated algorithm solution. 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