Authors : Hayder M. Naji and Ghaidaa A. Al-Sultany
Abstract: Basically, the PageRank algorithms set the inputted items with initial ranks. They usually use a normal distribution of initial rank in the item’s space with the ratio of 1/n for each item where n is the number of items in the dataset. Alternatively, a dynamic distribution of initial ranks according to the user preferences and item’s features has been proposed for recommendation system improving. The adapted PageRank algorithm was evaluated in comparis on with the traditional algorithm. The results were extremely encouraging with respect to the recommendation system improvement. The evaluation measures ofthe suggested algorithm were examined on the MovieLens dataset.
Hayder M. Naji and Ghaidaa A. Al-Sultany, 2017. Leveraging Personalized PageRank with Dynamic Initial Rank for Recommendation System Advances. Journal of Engineering and Applied Sciences, 12: 6487-6491.