Social Perception with Graph Attention Network for Recommendation Article Swipe
Jielin Jiang
,
Pengcheng Guo
,
Xiaolong Xu
,
Jintao Wu
,
Yan Cui
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1145/3665503
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1145/3665503
Recommendation systems are designed to uncover users’ potential preferences and make recommendations. However, they often face challenges such as data sparsity and the cold start problem. Although the introduction of knowledge graphs has partially addressed the issue of data sparsity, the challenge of cold start has not been effectively resolved. In this article, a novel approach called Social Perception with Graph Attention Network (SPGAT) for Recommendation is proposed. In SPGAT, we aim to leverage social perception to solve the cold start effectively for more accurate recommendations. The approach utilizes a multi-layer graph attention network to aggregate user preference features from collaborative knowledge graphs and social perception graphs. By analyzing the social network of a new user, associated friend users can be identified. The interaction data of these friend users is then provided as side information to recommend to the new user. To handle one-to-many and many-to-many relations, we introduce the TransD graph embedding model, which maps different types of relations and entities to different spaces. To optimize the proposed SPGAT, self-adversarial negative sampling is utilized to implement entity and relation embedding and generate negative samples. Experimental results demonstrate that SPGAT has achieved superior performance compared to several advanced methods.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1145/3665503
- https://dl.acm.org/doi/pdf/10.1145/3665503
- OA Status
- bronze
- Cited By
- 3
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4398179368
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4398179368Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1145/3665503Digital Object Identifier
- Title
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Social Perception with Graph Attention Network for RecommendationWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-05-21Full publication date if available
- Authors
-
Jielin Jiang, Pengcheng Guo, Xiaolong Xu, Jintao Wu, Yan CuiList of authors in order
- Landing page
-
https://doi.org/10.1145/3665503Publisher landing page
- PDF URL
-
https://dl.acm.org/doi/pdf/10.1145/3665503Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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bronzeOpen access status per OpenAlex
- OA URL
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https://dl.acm.org/doi/pdf/10.1145/3665503Direct OA link when available
- Concepts
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Perception, Computer science, Graph, Social network (sociolinguistics), Cognitive psychology, Psychology, Data science, World Wide Web, Theoretical computer science, Social media, NeuroscienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3Per-year citation counts (last 5 years)
- References (count)
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35Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/10 |
| sustainable_development_goals[0].score | 0.5299999713897705 |
| sustainable_development_goals[0].display_name | Reduced inequalities |
| citation_normalized_percentile.value | 0.83530585 |
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| citation_normalized_percentile.is_in_top_10_percent | False |