Convolutional Transformer Neural Collaborative Filtering Article Swipe
Pang Li
,
Shahrul Azman Mohd Noah
,
Hafiz Mohd Sarim
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2412.01376
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2412.01376
In this study, we introduce Convolutional Transformer Neural Collaborative Filtering (CTNCF), a novel approach aimed at enhancing recommendation systems by effectively capturing high-order structural information in user-item interactions. CTNCF represents a significant advancement over the traditional Neural Collaborative Filtering (NCF) model by seamlessly integrating Convolutional Neural Networks (CNNs) and Transformer layers. This sophisticated integration enables the model to adeptly capture and understand complex interaction patterns inherent in recommendation systems. Specifically, CNNs are employed to extract local features from user and item embeddings, allowing the model to capture intricate spatial dependencies within the data. Furthermore, the utilization of Transformer layers enables the model to capture long-range dependencies and interactions among user and item features, thereby enhancing its ability to understand the underlying relationships in the data. To validate the effectiveness of our proposed CTNCF framework, we conduct extensive experiments on two real-world datasets. The results demonstrate that CTNCF significantly outperforms state-of-the-art approaches, highlighting its efficacy in improving recommendation system performance.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2412.01376
- https://arxiv.org/pdf/2412.01376
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4405034230
All OpenAlex metadata
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https://openalex.org/W4405034230Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2412.01376Digital Object Identifier
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Convolutional Transformer Neural Collaborative FilteringWork title
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preprintOpenAlex work type
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enPrimary language
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2024Year of publication
- Publication date
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2024-12-02Full publication date if available
- Authors
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Pang Li, Shahrul Azman Mohd Noah, Hafiz Mohd SarimList of authors in order
- Landing page
-
https://arxiv.org/abs/2412.01376Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2412.01376Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2412.01376Direct OA link when available
- Concepts
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Convolutional neural network, Transformer, Computer science, Artificial intelligence, Natural language processing, Electrical engineering, Engineering, VoltageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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