相关实验视频
Updated: Jun 6, 2025

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Assessment of Social Transmission of Food Preferences Behaviors
Published on: January 25, 2018
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食品 公共意见 预防和控制模型 基于情绪分析
Leiyang Chen1,2, Xiangzhen Peng1,2, Liang Dong1,2
1Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, Wuhan 430001, China.
Foods (Basel, Switzerland)
|November 27, 2024
概括
本研究提出了一种深度学习模型,用于预测和管理食品公众论,增强消费者信任和食品安全. 食品公众论预防和控制 (FPOPC) 模型为监管机构提供了有效的情绪管理工具.
科学领域:
- 食品科学与技术 食品科学与技术
- 计算社会科学 计算社会科学
- 人工智能的人工智能是人工智能.
背景情况:
- 食品公众论对食品安全和消费者信任产生重大影响,原因是其快速传播和消极性.
- 现有的方法缺乏全面的策略来管理食品公众论的动态性质.
研究的目的:
- 开发和验证使用深度学习和推算法预防和控制食品公众论 (FPOPC) 模型.
- 通过积极管理公众情绪,增强食品安全和消费者信任.
主要方法:
- 制定了一个全面的FPOPC框架,涵盖了论发展的所有阶段.
- 利用堆叠自动编码器 (SAE) 根据用户评论预测食品新闻中的情绪.
- 实施了协作过推机制,并与HDFS一起增强了Bloom过器,以快速管理意见.
主要成果:
- FPOPC模型准确地预测和控制食品公众论的发展.
- 对食品新闻的情绪分析被有效量化并用于个性化的建议.
- 实验验证证了该模型在整个供应链中管理食品公众情绪方面的有效性.
结论:
- FPOPC模型为预测和控制食品公众论提供了一个强大的解决方案.
- 这种方法为监管机构提供了有价值的工具,以维护食品安全和消费者信心.
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