International Journal of Engineering

International Journal of Engineering

A Preference-based User Similarity to Construct a Collaborative Recommender System

Document Type : Original Article

Authors
B. Rahimpour Cami 1
H. Hassanpour 2
H. Mashayekhi 2
1 Faculty of Industrial and Computer Engineering, Mazandaran University of Science and Technology, Babol, Iran
2 Faculty of Computer Engineering, Shahrood University of Technology, Shahrood, Iran
10.5829/ije.2026.39.08b.17
Abstract
Recommender systems have emerged as indispensable tools to overcome the information overload on the web. These systems provide personalization for users to select favorite resources. Collaborative Filtering is among the popular approaches is widely used to construct recommender systems. The main challenge of this approach is the effectiveness of its similarity measure to find similar users/items for providing recommendations. In this paper, we propose a novel measure to compute the similarity considering users'' preferences. The proposed similarity measure improves the performance of recommender systems by incorporating high level latent factors instead of co-rated items by users, or common selection patterns. These latent factors are extracted via preference-based user modeling. It also provides a better recommendation when only a few ratings (sparse dataset) are available for similarity calculation. We implemented the proposed method and evaluated it using the MovieLens dataset. The evaluation results show that the proposed preference-based similarity measure considerably improves recommendation performance compared to other existing approaches.

Graphical Abstract

A Preference-based User Similarity to Construct a Collaborative Recommender System
Keywords
Collaborative Filtering User Similarity Similarity Measure   User Preferences

Subjects

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International Journal of Engineering
Volume 39, Issue 8
TRANSACTIONS B: Applications
August 2026
Pages 2012-2021