Parallel and Distributed Collaborative Filtering: A Survey
It addresses the need for scalable and efficient recommender systems, but is incremental as it reviews existing work without introducing new methods.
This survey compiles parallel and distributed implementations of collaborative filtering algorithms for recommender systems, aiming to present the field's development and highlight future research directions.
Collaborative filtering is amongst the most preferred techniques when implementing recommender systems. Recently, great interest has turned towards parallel and distributed implementations of collaborative filtering algorithms. This work is a survey of the parallel and distributed collaborative filtering implementations, aiming not only to provide a comprehensive presentation of the field's development, but also to offer future research orientation by highlighting the issues that need to be further developed.