Clustering-Based Collaborative Filtering Using an Incentivized/Penalized User Model

no code implementations • 1 May 2019 • Cong Tran, Jang-Young Kim, Won-Yong Shin, Sang-Wook Kim

As collaborative filtering (CF) is one of the most prominent and popular techniques used for recommender systems, we propose a new clustering-based CF (CBCF) method using an incentivized/penalized user (IPU) model only with ratings given by users, which is thus easy to implement.

Clustering Collaborative Filtering +1