Recommendation system based on collaborative filtering in RapidMiner

Zhihang Tang, Zhonghua Wen

School of Computer and Communication, Hunan Institute of Engineering Xiangtan 411104, China

Recommender systems facilitate decision-making processes through informed assistance and enhanced user experience. To aid in the decision-making process, recommender systems use the available data on the items themselves. Personalized recommender systems subsequently use this input data, and convert it to an output in the form of ordered lists or scores of items in which a user might be interested. These lists or scores are the final result the user will be presented with, and their goal is to assist the user in the decision-making process. The application of recommender systems outlined was just a small introduction to the possibilities of the extension. Recommender systems became essential in an information- and decision-overloaded world. They changed the way users make decisions, and helped their creators to increase revenue at the same time. Bringing recommender systems to a broader audience is essential in order to popularize them beyond the limits of scientific research and high technology entrepreneurship. The recommender systems will assist you in reaching quality, informed decisions.