3 citations · 3 across the 3 of their papers we have counts for
5 papers
Hybrid Movie Recommender System based on Resource Allocation
Mostafa Khalaji, Chitra Dadkhah, Joobin Gharibshah
Recommender Systems are inevitable to personalize user's experiences on the Internet. They are using different approaches to recommend the Top-K items to users according to their p…
TRSM-RS: A Movie Recommender System Based on Users' Gender and New Weighted Similarity Measure
Mostafa Khalaji
With the growing data on the Internet, recommender systems have been able to predict users' preferences and offer related movies. Collaborative filtering is one of the most popular…
FNHSM_HRS: Hybrid recommender system using fuzzy clustering and heuristic similarity measure
Mostafa Khalaji, Chitra Dadkhah
Nowadays, Recommender Systems have become a comprehensive system for helping and guiding users in a huge amount of data on the Internet. Collaborative Filtering offers to active us…
CUPCF: Combining Users Preferences in Collaborative Filtering for Better Recommendation
Mostafa Khalaji, Nilufar Mohammadnejad
How to make the best decision between the opinions and tastes of your friends and acquaintances? Therefore, recommender systems are used to solve such issues. The common algorithms…
FCNHSMRA_HRS: Improve the performance of the movie hybrid recommender system using resource allocation approach
Mostafa Khalaji, Nilufar Mohammadnejad
Recommender systems are systems that are capable of offering the most suitable services and products to users. Through specific methods and techniques, the recommender systems try…