Research on the Design of Information Resource Automatic Classification and Recommendation System Based on Deep Learning

Research Article
Open access

Research on the Design of Information Resource Automatic Classification and Recommendation System Based on Deep Learning

Xiao Han 1*
  • 1 Shungeng Campus, University of Jinan, No. 13 Shungeng Road, Shunyulu Subdistrict, Shizhong District, Jinan City, Shandong Province    
  • *corresponding author 19153103170@163.com
ACE Vol.166
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-80590-177-8
ISBN (Online): 978-1-80590-178-5

Abstract

This article proposes a framework for automatic classification and recommendation of information resources based on deep learning. Through neural networks and natural language processing techniques, automatic classification of information resources can be effectively achieved, and personalized suggestions can be provided based on user behavior and semantic features of items. The classification adopts a combination of convolutional neural network and long short-term memory network for more accurate localization of text labels; The combination of deep learning collaboration and content recommendation algorithm is recommended to improve the recommendation effect. The experiment shows that this design method has improved accuracy and recommendation effectiveness compared to traditional classification and recommendation methods, and has the advantages of high accuracy and high real-time performance, which can meet the needs of information processing in large-scale data processing.

Keywords:

Deep learning, Information resources, Automatic classification, Recommendation system, Data mining

Han,X. (2025). Research on the Design of Information Resource Automatic Classification and Recommendation System Based on Deep Learning. Applied and Computational Engineering,166,31-35.
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References

[1]. Krishnamoorthi S , Shyam G K .DESIGN OF RECOMMENDENDATION SYSTEMS USING DEEP REINFORCEMENT LEARNING – RECENT ADVANCEMENTS AND APPLICATIONS[J].journal of theoretical and applied information technology, 2024, 102(7):2908-2923.

[2]. Zhao Y , Zhao H .RESEARCH ON DATA MINING AND REINFORCEMENT LEARNING IN RECOMMENDATION SYSTEMS[J].Scalable Computing: Practice & Experience, 2024, 25(3).

[3]. Gündoan, Esra, Kaya M , Daud A .Deep learning for journal recommendation system of research papers[J].Scientometrics, 2023, 128(1):461-481.

Cite this article

Han,X. (2025). Research on the Design of Information Resource Automatic Classification and Recommendation System Based on Deep Learning. Applied and Computational Engineering,166,31-35.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of CONF-SEML 2025 Symposium: Machine Learning Theory and Applications

ISBN：978-1-80590-177-8(Print) / 978-1-80590-178-5(Online)
Editor：Hui-Rang Hou
Conference website: https://2025.confseml.org/tianjin.html
Conference date: 18 May 2025
Series: Applied and Computational Engineering
Volume number: Vol.166
ISSN：2755-2721(Print) / 2755-273X(Online)

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References

[1]. Krishnamoorthi S , Shyam G K .DESIGN OF RECOMMENDENDATION SYSTEMS USING DEEP REINFORCEMENT LEARNING – RECENT ADVANCEMENTS AND APPLICATIONS[J].journal of theoretical and applied information technology, 2024, 102(7):2908-2923.

[2]. Zhao Y , Zhao H .RESEARCH ON DATA MINING AND REINFORCEMENT LEARNING IN RECOMMENDATION SYSTEMS[J].Scalable Computing: Practice & Experience, 2024, 25(3).

[3]. Gündoan, Esra, Kaya M , Daud A .Deep learning for journal recommendation system of research papers[J].Scientometrics, 2023, 128(1):461-481.

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