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Parham Moradi

Parham Moradi

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId: 654
Faculty: Faculty of Engineering
Address: Department of Computer Engineering, Faculty of Engineering, University of Kurdistan
Phone:

Research

Title
A collaborative filtering method based on genetic algorithm and trust statements
Type
Presentation
Keywords
collaborative filtering, genetic algorithm, trust information
Year
2018
Researchers Shahrokh Esmaeili ، Hashem Parvin ، Parham Moradi

Abstract

Collaborative Filtering (CF) is a frequently used recommendation method that has been successfully applied on many real-world systems. An important problem in CF is selecting a proper set of users and employing them in the rating prediction. Most of current similarity metrics incorporate only the rating values and ignore other information sources in their calculations; while in most of real-world systems, there are sparse data. To tackle this issue, in this paper, a two-step CF method called TCFGA is proposed to provide a set of similar users. In addition, their importance is weighed by employing social trust statements along with rating values. To evaluate the effectiveness of TCFGA, several experiments are performed on two real-world datasets and obtained results show the superiority of TCFGA compared to the others.