عنوان	Evolutionary based matrix factorization method for collaborative filtering systems
نوع پژوهش	مقاله ارائه شده کنفرانسی
کلیدواژه‌ها	Recommender System, Collaborative filtering, Matrix factorization, Genetic algorithm.
چکیده	The Matrix-Factorization (MF) based models have become popular when building Collaborative Filtering (CF) recommender systems, due to the high accuracy and scalability. Most of nowadays matrix factorization models don't have acceptable execution time during to large datasets. In this article, we introduce a new collaborative filtering recommender system, based on matrix factorization by using genetic algorithm.
پژوهشگران	داریوش زندی (نفر اول)، پرهام مرادی دولت آبادی (نفر دوم)، فردین اخلاقیان طاب (نفر سوم)