A Heterogeneous Information Networks with an Attention Mechanism for Improving Recommender Systems

Heidari, Narges; Moradi, Parhamam

doi:10.24271/psr.2024.457153.1596

A Heterogeneous Information Networks with an Attention Mechanism for Improving Recommender Systems

Document Type : Review Article

Authors

Narges Heidari ¹

Parhamam Moradi ²

¹ Department of Computer Engineering, Ilam Branch, Islamic Azad University, Tehran, Iran

² Department of Computer Engineering, University of Kurdistan, Sanandaj, Iran

10.24271/psr.2024.457153.1596

Abstract

This manuscript present an attention-based recommender system based on heterogeneous information networks (HINs). Our method utilizes meta-paths to extract user and item representations. Furthermore, it employs a language model to capture long-range dependencies within the review texts. The attention mechanism is applied to assess the significance of each review text. Finally, it utilizes matrix factorization framework to model interactions between users and items with the aim of predicting the ratings of users on items. To evaluate the effectiveness of the proposed method several experiments were conducted on two well-known datasets. the obtained results indicate the superiority of the proposed method compared to the state-of-the-art methods.

Keywords

Attention Mechanism

Heterogeneous Information Networks

Meta-paths

Recommender Systems