This document summarizes a research paper that proposes a scalable collaborative filtering framework based on co-clustering. It introduces a dynamic collaborative filtering approach that supports new users, items, and ratings using incremental and batch versions of the co-clustering algorithm. Experimental results on a movie rating dataset show the co-clustering approach provides comparable prediction accuracy to SVD, NNMF, and correlation-based methods but with much lower computational effort.