Hayder  M. Naji, Ghaidaa  A. Al-Sultany, 
    Collaborative Filtering Recommendation using Personalized Page Rank
Algorithm with New Personalized Parameters,
    Journal of Engineering and Applied Sciences,
    Volume 12,Issue 16,
    2017,
    Pages 4108-4112,
    ISSN 1816-949x,
    jeasci.2017.4108.4112,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2017.4108.4112)
    Abstract: Collaborative filtering recommendation system shares the user’s interests and recommends items to
a user based on the interests of the other users whom are similar to his/her owntendencies. Basically, the
Personalized Page Rank Algorithm (PPR) suggests items with respect to the target user by personalizing him/her
only. In this study, Iteratively with each target user, the remaining users are personalized according to their
rating patterns by supporting them withnew Personalized Parameters (PP). The personalized parameters have
a role of personalized measure from which each user’s rank will affect and be affected on the other
user’s ranks depending on the PP values. The achievement of more accurate recommender system needsmore
personalization to satisfy user’s tendencies so we Present a Personalized Recommendation system using PPR
algorithm with more personalization method. Finally, classification accuracy measures have been used to
evaluate the outcome top-N recommendation list on a MovieLens dataset in comparison with the outcome of
traditional PPR.
    Keywords: collaborative filtering;personalized parameters;personalized page rank;Recommendation system;accurate