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Dual-path recommendation algorithm based on CNN and attention-enhanced LSTM.
- Source :
-
Cyber-Physical Systems . Jul2024, Vol. 10 Issue 3, p247-262. 16p. - Publication Year :
- 2024
-
Abstract
- To recommend useful information to users more efficiently, this paper proposes a dual-path recommendation algorithm which combines multilayer Convolutional Neural Network (CNN) and attention-enhanced long short-term memory network (Attention-LSTM). Firstly, the matrix factorisation technique is used for learning the long-term preferences of users. Secondly, a dual-path network based on CNN and LSTM is constructed to perform feature extraction on the rating matrix. The dual-path network can learn the long-term preferences of users while capturing their dynamic preferences in changing preferences. The algorithm is tested on the public dataset MovieLens-1M, and the MAE value reflects the accuracy of the algorithm. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 23335777
- Volume :
- 10
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Cyber-Physical Systems
- Publication Type :
- Academic Journal
- Accession number :
- 177519964
- Full Text :
- https://doi.org/10.1080/23335777.2023.2177750