Session Recommendation Based on Edge Information Clustering Article Swipe
Manfu Ma
,
Dongliang Yang
,
Yong Li
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2363/1/012003
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2363/1/012003
Traditional session recommendation mainly uses the time sequence of users clicking items to construct a user session graph, which often ignores the similarity and differences between user groups. To improve the effect of recommendation, an E-SGNN (E-SGNN, Edge-Session Graph Neural Network) method combining edge information clustering and session recommendation is proposed. Firstly, similar users are clustered by edge information and divided into different session user groups. After extracting the data features of the user site relationship graph in the session, it is reset and updated through the gated graph neural network (GGNN); Secondly, a self-attention mechanism is introduced to adjust the proportion of users’ current preference and historical preference; Finally, the ranking score is obtained through linear transformation and softmax classifier. The higher the score, the more obvious the user’s preference for the item. Experiments show that compared with session-based graph neural network and cross-session information recommendation, the E-SGNN algorithm proposed in this paper has a significant improvement in recall rate and average reciprocal ranking. When the three edge parameters are combined, the recall rate reaches 98.97% and the average reciprocal ranking reaches 45.77%.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/2363/1/012003
- https://iopscience.iop.org/article/10.1088/1742-6596/2363/1/012003/pdf
- OA Status
- diamond
- Cited By
- 1
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4308524683
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https://openalex.org/W4308524683Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/1742-6596/2363/1/012003Digital Object Identifier
- Title
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Session Recommendation Based on Edge Information ClusteringWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-11-01Full publication date if available
- Authors
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Manfu Ma, Dongliang Yang, Yong LiList of authors in order
- Landing page
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https://doi.org/10.1088/1742-6596/2363/1/012003Publisher landing page
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https://iopscience.iop.org/article/10.1088/1742-6596/2363/1/012003/pdfDirect link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://iopscience.iop.org/article/10.1088/1742-6596/2363/1/012003/pdfDirect OA link when available
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Computer science, Session (web analytics), Cluster analysis, Information retrieval, Graph, Artificial intelligence, Theoretical computer science, World Wide WebTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2023: 1Per-year citation counts (last 5 years)
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35Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.clustered | 55 |
| abstract_inverted_index.combined, | 171 |
| abstract_inverted_index.combining | 42 |
| abstract_inverted_index.construct | 13 |
| abstract_inverted_index.different | 62 |
| abstract_inverted_index.mechanism | 95 |
| abstract_inverted_index.proposed. | 50 |
| abstract_inverted_index.clustering | 45 |
| abstract_inverted_index.extracting | 67 |
| abstract_inverted_index.historical | 107 |
| abstract_inverted_index.introduced | 97 |
| abstract_inverted_index.parameters | 169 |
| abstract_inverted_index.preference | 105, 130 |
| abstract_inverted_index.proportion | 101 |
| abstract_inverted_index.reciprocal | 163, 180 |
| abstract_inverted_index.similarity | 22 |
| abstract_inverted_index.Experiments | 134 |
| abstract_inverted_index.Traditional | 0 |
| abstract_inverted_index.classifier. | 120 |
| abstract_inverted_index.differences | 24 |
| abstract_inverted_index.improvement | 157 |
| abstract_inverted_index.information | 44, 58, 145 |
| abstract_inverted_index.preference; | 108 |
| abstract_inverted_index.significant | 156 |
| abstract_inverted_index.Edge-Session | 37 |
| abstract_inverted_index.relationship | 75 |
| abstract_inverted_index.cross-session | 144 |
| abstract_inverted_index.session-based | 139 |
| abstract_inverted_index.recommendation | 2, 48 |
| abstract_inverted_index.self-attention | 94 |
| abstract_inverted_index.transformation | 117 |
| abstract_inverted_index.recommendation, | 33, 146 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5017384189 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I68986083 |
| citation_normalized_percentile.value | 0.62834468 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |