Geography and Regional Planning

Geography and Regional Planning

Development of an Intelligent Recommender System with a group Refinement approach based on Geographic Data Modeling

Authors
Tahereh Kheradmandan 1
Farhad Mardukhi 2
Amir Khiekh Ahmadi 3
1 PhD student, Computer Science Department, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran
2 Assistant Professor, Department of Computer Engineering and Information Technology, Razi University, Kermanshah, Iran
3 Department of Computer Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran
10.22034/jgeoq.2025.551855.4347
Abstract
The main objective of this research is to design and implement an intelligent recommender system using GIS modeling data to improve the quality of recommendations in online sales systems. The selected research method is the scientific design and experimental research method, in which, in the evaluation stage of the scientific design research method, experimental design has been used. To improve the performance of the intelligent recommender system, user-defined labels and deep neural network algorithms along with GIS modeling have been used to generate recommendations. In the designed and conducted experiment, the label-based recommender system (which is designed and created to generate recommendations) is compared with the group filtering recommender system (which is a conventional and benchmark recommender system) in the evaluation criteria of precision, recall, and F1. Based on the results, the proposed recommender system based on the group filtering method and GIS data based on deep neural networks performs better than the group filtering system in all these evaluation criteria.
Keywords
Development
Intelligent Recommender System
Group Refinement Approach
Geographic Data Modeling
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