一个基于情感分析的智能电影推系统
Wenzuixiong Xiong1, Yichao Zhang2
1School of art, Hubei University, Wuhan, Hubei, China.
PeerJ. Computer science
|June 22, 2023
概括
这项研究引入了一种新的个性化电影推系统,该系统分析了用户的评论情绪. 它克服了分级尺度的差异,提供了更准确,更引人入胜的电影建议.
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:
- 传统的个性化电影推依赖于用户评级,这些评级是主观的,差异很大.
- 这种主观性使得准确捕捉用户偏好和提供相关的电影建议具有挑战性.
- 挖掘用户评论情绪为了解真实用户偏好提供了一个有希望的替代方案.
研究的目的:
- 开发一种个性化的电影推方法,利用用户评论的情感分析.
- 解决现有推系统中主观用户评级尺度的局限性.
- 通过情感分析提高电影推的准确性和用户参与度.
主要方法:
- 利用自然语言处理 (NLP) 来从用户电影评论中提取情绪倾向.
- 实现了多模态情感特征的加权融合,使用粒子集群优化 (PSO) 进行了优化.
- 计算情感相似性,考虑内容发布时间和平均用户情绪,以产生顶级N推.
主要成果:
- 拟议的基于多模式情绪分析的推系统的表现优于比较方法.
- 该系统有效地缓解了因用户评级尺度不一致而产生的问题.
- 显示了用户对推电影的兴趣和参与度的增加.
结论:
- 用户评论的情感分析为个性化电影推提供了强大的方法.
- 开发的方法提供了一个优越的替代传统的基于评级的系统.
- 这种方法提高了电影推服务的质量和用户满意度.
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