ITNRM is a recommendation methodology proposed by Reza Barzegar Nozari and Hamidreza Koohi. It was published in Expert Systems With Application and is available online: https://doi.org/10.1016/j.eswa.2021.115709
This version is a primary code of the ITNRM by MATLAB. In this version, a main code has been presented for each dataset of Filmtrust, Ciao, and MoviLens 100K and 1M.
A description of ITNRM is available from https://docs.google.com/document/d/1NlfoQvzhTNGuEgkIPM8Tfb90FFepkbYql1FQkc4dxCM/edit?usp=sharing
We will appreciate if you cite our papers in your work:
[1] Barzegar Nozari, R., & Koohi, H. (2021). Novel implicit-trust-network-based recommendation methodology. Expert Systems with Applications, 186. https://doi.org/10.1016/j.eswa.2021.115709
[2] Barzegar Nozari, Reza, & Koohi, H. (2020). A novel group recommender system based on members’ influence and leader impact. Knowledge-Based Systems, 205, 106296. https://doi.org/10.1016/j.knosys.2020.106296
[3] Barzegar Nozari, R., Koohi, H., & Mahmodi, E. (2020). A novel trust computation method based on user ratings to improve the recommendation. International Journal of Engineering Transactions C: Aspects, 33(3), 377–386. https://doi.org/10.5829/ije.2020.33.03c.02