Survey on Evaluation of Recommender Systems (International Journal of Engineering and Computer Science, 2015)
Recommender Systems (RSs) can be found in many modern applications and that expose the user to a huge collections of itemsand helps user to decide on appropriate items, and ease the task of finding preferred items in the collection. Recently Recommender systemsare gaining popularity in both commercial and research community, where many algorithms have been used for providingrecommendations. There are many evaluation metrics used for comparing this recommendation algorithms. The literature on recommendersystem evaluation offers a large variety of evaluation metrics and choose most appropriate evaluation metric among them. Error-basedmetrics likes MAE, RMSE and Ranking-based metrics like Precision and Recall are discussed in this paper. Using this evaluation metricsevaluate the performance of recommender systems.