Sequential recommendation based on contrast enhanced time-aware self-attention mechanism
The existing sequence recommendation models have shortcomings in utilizing absolute interaction time, resulting in inaccurate modeling of user preferences. Sequential recommendation based on contrast enhanced time-aware self-attention mechanism (CTiSASRec) was proposed. Firstly, the calculation proc...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2025-01-01
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| Series: | Dianxin kexue |
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| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2025003/ |
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| _version_ | 1823864679781367808 |
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| author | YU Yang WANG Ruiqin |
| author_facet | YU Yang WANG Ruiqin |
| author_sort | YU Yang |
| collection | DOAJ |
| description | The existing sequence recommendation models have shortcomings in utilizing absolute interaction time, resulting in inaccurate modeling of user preferences. Sequential recommendation based on contrast enhanced time-aware self-attention mechanism (CTiSASRec) was proposed. Firstly, the calculation process of attention weights integrated rating data, absolute interaction time, location information, and project popularity. Secondly, the absolute interaction time and location order of the project were integrated to generate a new project location embedding. Finally, during the training process, contrast learning based on the results of two modeling sequences was used to distinguish the similarities and differences between samples, thereby improving the accuracy and robustness of the model. Experimental studies conducted on six datasets of different fields and scales show that CTiSASRec outperforms state-of-the-art sequential recommendation models. |
| format | Article |
| id | doaj-art-51998779476447188bc558fe2a4aff8b |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2025-01-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-51998779476447188bc558fe2a4aff8b2025-02-08T19:00:22ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012025-01-014113714782011726Sequential recommendation based on contrast enhanced time-aware self-attention mechanismYU YangWANG RuiqinThe existing sequence recommendation models have shortcomings in utilizing absolute interaction time, resulting in inaccurate modeling of user preferences. Sequential recommendation based on contrast enhanced time-aware self-attention mechanism (CTiSASRec) was proposed. Firstly, the calculation process of attention weights integrated rating data, absolute interaction time, location information, and project popularity. Secondly, the absolute interaction time and location order of the project were integrated to generate a new project location embedding. Finally, during the training process, contrast learning based on the results of two modeling sequences was used to distinguish the similarities and differences between samples, thereby improving the accuracy and robustness of the model. Experimental studies conducted on six datasets of different fields and scales show that CTiSASRec outperforms state-of-the-art sequential recommendation models.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2025003/sequential recommendationself-attentiontime-aware modelcontrast learning |
| spellingShingle | YU Yang WANG Ruiqin Sequential recommendation based on contrast enhanced time-aware self-attention mechanism Dianxin kexue sequential recommendation self-attention time-aware model contrast learning |
| title | Sequential recommendation based on contrast enhanced time-aware self-attention mechanism |
| title_full | Sequential recommendation based on contrast enhanced time-aware self-attention mechanism |
| title_fullStr | Sequential recommendation based on contrast enhanced time-aware self-attention mechanism |
| title_full_unstemmed | Sequential recommendation based on contrast enhanced time-aware self-attention mechanism |
| title_short | Sequential recommendation based on contrast enhanced time-aware self-attention mechanism |
| title_sort | sequential recommendation based on contrast enhanced time aware self attention mechanism |
| topic | sequential recommendation self-attention time-aware model contrast learning |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2025003/ |
| work_keys_str_mv | AT yuyang sequentialrecommendationbasedoncontrastenhancedtimeawareselfattentionmechanism AT wangruiqin sequentialrecommendationbasedoncontrastenhancedtimeawareselfattentionmechanism |