/Streaming-Recommender-System

The increasing popularity of real-world recommender systems produces data continuously and rapidaly, and it becomes more realistic to study recommender systems under streaming scenarious. This project mainly deal with the problem of recommendation with stream inputs. Experimental results have been performed in real world datasets- netflix and movielens. We have performed dimensionality redcution using popular alogorithm such as SVD, KNNbaseline, PMF, GPFM etc and performance have been calculated on the basis of RMSE.

Primary LanguageJupyter Notebook

Streaming-Recommender-System

The increasing popularity of real-world recommender systems produces data continuously and rapidaly, and it becomes more realistic to study recommender systems under streaming scenarious. This project mainly deal with the problem of recommendation with stream inputs. Experimental results have been performed in real world datasets- netflix and movielens. We have performed dimensionality redcution using popular alogorithm such as SVD, KNNbaseline, PMF, GPFM etc and performance have been calculated on the basis of RMSE.