Recommendation Algorithm in Double-Layer Network Based on Vector Dynamic Evolution Clustering and Attention Mechanism
The purpose of recommendation systems is to help users find effective information quickly and conveniently and also to present the items that users are interested in. While the literature of recommendation algorithms is vast, most collaborative filtering recommendation approaches attain low recommen...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/5206087 |
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| _version_ | 1832550841316278272 |
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| author | Jianrui Chen Zhihui Wang Tingting Zhu Fernando E. Rosas |
| author_facet | Jianrui Chen Zhihui Wang Tingting Zhu Fernando E. Rosas |
| author_sort | Jianrui Chen |
| collection | DOAJ |
| description | The purpose of recommendation systems is to help users find effective information quickly and conveniently and also to present the items that users are interested in. While the literature of recommendation algorithms is vast, most collaborative filtering recommendation approaches attain low recommendation accuracies and are also unable to track temporal changes of preferences. Additionally, previous differential clustering evolution processes relied on a single-layer network and used a single scalar quantity to characterise the status values of users and items. To address these limitations, this paper proposes an effective collaborative filtering recommendation algorithm based on a double-layer network. This algorithm is capable of fully exploring dynamical changes of user preference over time and integrates the user and item layers via an attention mechanism to build a double-layer network model. Experiments on Movielens, CiaoDVD, and Filmtrust datasets verify the effectiveness of our proposed algorithm. Experimental results show that our proposed algorithm can attain a better performance than other state-of-the-art algorithms. |
| format | Article |
| id | doaj-art-752afe03d41646d5aaada33017ecb21d |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-752afe03d41646d5aaada33017ecb21d2025-02-03T06:05:41ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/52060875206087Recommendation Algorithm in Double-Layer Network Based on Vector Dynamic Evolution Clustering and Attention MechanismJianrui Chen0Zhihui Wang1Tingting Zhu2Fernando E. Rosas3Key Laboratory of Modern Teaching Technology, Ministry of Education, Xi’an, ChinaSchool of Computer Science, Shaanxi Normal University, Xi’an, ChinaSchool of Computer Science, Shaanxi Normal University, Xi’an, ChinaData Science Institute and Department of Brain Science, Imperial College London, London, UKThe purpose of recommendation systems is to help users find effective information quickly and conveniently and also to present the items that users are interested in. While the literature of recommendation algorithms is vast, most collaborative filtering recommendation approaches attain low recommendation accuracies and are also unable to track temporal changes of preferences. Additionally, previous differential clustering evolution processes relied on a single-layer network and used a single scalar quantity to characterise the status values of users and items. To address these limitations, this paper proposes an effective collaborative filtering recommendation algorithm based on a double-layer network. This algorithm is capable of fully exploring dynamical changes of user preference over time and integrates the user and item layers via an attention mechanism to build a double-layer network model. Experiments on Movielens, CiaoDVD, and Filmtrust datasets verify the effectiveness of our proposed algorithm. Experimental results show that our proposed algorithm can attain a better performance than other state-of-the-art algorithms.http://dx.doi.org/10.1155/2020/5206087 |
| spellingShingle | Jianrui Chen Zhihui Wang Tingting Zhu Fernando E. Rosas Recommendation Algorithm in Double-Layer Network Based on Vector Dynamic Evolution Clustering and Attention Mechanism Complexity |
| title | Recommendation Algorithm in Double-Layer Network Based on Vector Dynamic Evolution Clustering and Attention Mechanism |
| title_full | Recommendation Algorithm in Double-Layer Network Based on Vector Dynamic Evolution Clustering and Attention Mechanism |
| title_fullStr | Recommendation Algorithm in Double-Layer Network Based on Vector Dynamic Evolution Clustering and Attention Mechanism |
| title_full_unstemmed | Recommendation Algorithm in Double-Layer Network Based on Vector Dynamic Evolution Clustering and Attention Mechanism |
| title_short | Recommendation Algorithm in Double-Layer Network Based on Vector Dynamic Evolution Clustering and Attention Mechanism |
| title_sort | recommendation algorithm in double layer network based on vector dynamic evolution clustering and attention mechanism |
| url | http://dx.doi.org/10.1155/2020/5206087 |
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