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Name: Reza Barzegar Nozari
Type: User
Twitter: BarzegarNozari
Name: Reza Barzegar Nozari
Type: User
Twitter: BarzegarNozari
This repository explores collaborative filtering (CF) techniques by implementing the approaches described in "Improving Collaborative Filtering Performance: A Comparative Analysis of Clustering Algorithms with and without Autoencoders".
IBGR (Influence-Based Group Recommendation) is a novel group recommendation that published in Knowledge-Based System journal at Elsevier. It takes into account the influence of members and leaders in groups to determine items rating proper to all members for groups. There is a sample MATLAB code of IBGR for a fixed group with 4 member and 7 items.
This repository contains a Python script that implements a novel group recommender system based on the research paper titled "A novel group recommender system based on members’ influence and leader impact" by Reza Barzegar Nozari and Hamidreza Koohi.
The codes have been provided to support the article "Novel implicit-trust-network-based recommendation methodology", which has been published in Expert Systems With Applications. This algorithmic framework is abbreviated to ITNRM. It first generates implicit trust networks to find users' trustees or neighbors. And a novel recommendation methodology is implemented to find suitable items closed to the users' preferences. Finally, datasets, i.e., MovieLens, Ciao, and FilmTrust are used for experiments.
This repository contains Python code that implements a trust-based collaborative filtering approach for enhancing rating predictions in recommendation systems. The methodology is based on the research paper titled "Novel Implicit-Trust-Network-based Recommendation Methodology" by Reza Barzegar Nozari and Hamidreza Koohi.
This repository contains two implementations of a K-Nearest Neighbors (KNN) classifier for predicting online shopping behavior. The classifiers are implemented in Python and use different approaches for finding the nearest neighbors: Naive Implementation, KDTree Implementation
This repository will contain Python scripts implementing soft fair aggregation and soft group formation methods for group recommendation.
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