情感和情感丰富的决策转换器,提供个性化的建议
Sana Abakarim1, Sara Qassimi2, Said Rakrak2
1L2IS Laboratory, Faculty of Science and Techniques, Cadi Ayyad University, Marrakesh, Morocco. sana.abakarim@ced.uca.ma.
Scientific reports
|July 2, 2025
概括
我们介绍了情感和情感丰富的决策转换器 (ESE-DT),这是一个新的推系统,使用情感和情感分析来提高用户参与度. 在现实世界数据集上,ESE-DT显著优于现有的方法.
科学领域:
- 人工智能的人工智能
- 自然语言处理自然语言处理.
- 推系统是一个推系统.
背景情况:
- 传统的推系统很难将用户的情绪和情绪从评论中结合起来.
- 提高用户参与度和满意度取决于理解微妙的情感内容.
研究的目的:
- 提出一种新的框架,即情感和情感丰富的决策转换器 (ESE-DT),用于连续推.
- 将情感和情感分析集成到决策转换器 (DT) 框架中,以提高上下文理解.
主要方法:
- 用决策转换器 (DT) 框架将推任务重新想象为轨迹建模问题.
- 利用先进的自然语言处理 (NLP) 来提取情感和情感,以丰富用户和项目嵌入.
- 在Yelp和谷歌本地评论数据集上实验验验证ESE-DT.
主要成果:
- 在这两种数据集上,与最先进的基线相比,ESE-DT表现优越.
- 在关键指标方面取得了显著的改进:在nDCG@10上达到了11.76%,在Yelp上的HR@10上达到了11.58%.
- 在Yelp上RMSE大幅降低了42.11%,在谷歌本地评论上降低了17.43%.
结论:
- 拟议的ESE-DT框架有效地将情感和情感分析集成到顺序推中.
- 通过捕捉时间动态和用户的上下文理解,ESE-DT增强了个性化的建议.
- 调查结果强调了ESE-DT在推进智能城市个性化服务方面的潜力.
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