* Cross-System Collaborative Filtering where user profiles across multiple recommender systems are combined in a privacy preserving manner.

* Robust Collaborative Filtering, where recommendation is stable towards efforts of manipulation.

* Content-Boosted Collaborative Filtering for Improved Recommendations.

* Eigentaste: A Constant Time Collaborative Filtering Algorithm.

* A Survey of Collaborative Filtering Techniques Su, Xiaoyuan and Khoshgortaar, Taghi.

* Google News Personalization: Scalable Online Collaborative Filtering Abhinandan Das, Mayur Datar, Ashutosh Garg, and Shyam Rajaram.

* Factor in the Neighbors: Scalable and Accurate Collaborative Filtering Yehuda Koren, Transactions on Knowledge Discovery from Data ( TKDD ) ( 2009 )

* Rating Prediction Using Collaborative Filtering

One of the most famous examples of Collaborative Filtering is item-to-item collaborative filtering ( people who buy x also buy y ), an algorithm popularized by Amazon. com's recommender system.

( 2002 ) Content-Boosted Collaborative Filtering for Improved Recommendations.

* Nasraoui O., Cerwinske J., Rojas C., and Gonzalez F., " Collaborative Filtering in Dynamic Usage Environments ", in Proc.