Design of Resource Intelligent Systems Recommendation Algorithm and System Based on Heterogeneous Network Representation Learning

Authors

  • Jiana Bi School of Software and Big Data, Changzhou College of Information Technology, Changzhou 213164, Jiangsu, China

Abstract

Based on the historical behavior data ofusers, the recommendation systemfilters outvaluable information from complex data andactively recommends resources for users, so that they can obtain resources quickly and accurately. This effectively solves the problem of information overload in the Internet era, and improves the efficiency of resource use. A heterogeneous information network can naturally model the complex objects and their rich relationships in the recommendation system, and explore the potential connections between users by analyzing different types of relationship paths.
This paper focuses on two issues: Firstly, the recommendation algorithm is studied, including recommendation algorithm design, model training design, experimental data set selection, evaluation index design, and the superiority of the algorithm is verified through experiments. Then we study the recommendation system, design the simulation function which consists of the recommendation use subsystem and the recommendation management subsystem, and verify the validity of the software through the system test.

Keywords: heterogeneous network representation learning; resource recommendation algorithm; system design; random walk; Skip-Gram model; experiment and testing

Cite As

J. Bi, "Design of Resource Intelligent Systems Recommendation Algorithm and System Based on Heterogeneous Network Representation Learning", Engineering Intelligent Systems, vol. 34 no. 3, pp. 353-359, 2026.

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Published

2026-05-01

Issue

Vol. 34 No. 3 (2026): International Journal of Engineering Intelligent Systems

Section

Article

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