百科电影评论的情感分析：一种新的基于特征的启发式情感分类方法

一种新的基于特征的启发式情感分类方法 1
摘要 1

  1. 介绍 1
  2. 算法公式 2
  3. 观察结论 4
  4. 观察结论
    我们的实验工作有两项重要贡献。首先，探讨了“副词+动词”与“副词+形容词”的组合在文本级情绪分类中的应用。其次，提出了一种新的基于特征的启发式电影情感分类方法。方面级别的情感分类产生了一个准确和容易理解的电影情感概况。有趣的是，方面级别的情感分析结果与电影评论的文本层面的情感分类是一致的。尽管如此，方面层面的情感概况可以为特定的电影提供更为集中和准确的情感总结，并且对用户更为有用。
    我们设计的方面情感分析算法公式是一种从多个评价的不同方面获得电影完整情感轮廓的新颖独特的方法。由此产生的情绪概况信息丰富，易于理解，对用户非常有用。此外，用于方面级情绪分析的算法公式非常简单，实现速度快，生成结果快，不需要任何的培训。它可以在运行中使用，并在感兴趣的各个方面展示非常有用和详细的电影情感概况。这部分实现还可以使用内容过滤、协作过滤或混合方法作为电影推荐系统中的附加步骤。情感档案可作为设计适当电影推荐系统的额外过滤步骤。这一层面的情绪分析是一种有价值的情绪分析形式，也是随后大量用户对特定电影所表达信息的利用。这个方面算法实现的唯一限制是它是特定于域的，然而，在不同的领域中使用这种算法公式只需要很少的变化（在方面向量中）。

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