基于约束型LDA的评价对象-情感词关联关系提取

Extraction of Association Relationship between Evaluation Object and Emotion Words Based on Constrained LDA

随着社交媒体的发展,网络上产生了大量的评论类文本数据,这些数据蕴含了丰富的情感信息。对这些文本数据进行情感极性分类,需要提取评价对象-情感词的匹配关系。文章提出了基于约束LDA主题模型的评价对象-情感词关系提取模型CE-LDA,将语义先验知识嵌入到LDA模型,在有效提取评价对象和情感词的同时,发现它们之间的关联性。通过实验分析,CE-LDA模型对于评价对象和情感词及其关联关系的提取具有较好的效果。

With the development of social media,a large amount of comment text data has been generated on the internet,which contain rich emotion information.To classify the sentiment polarity of these text data,it is necessary to extract the matching relationship between the evaluation object and the emotion words.An the evaluation object and the emotion words relationship extracting model CELDA based on the constrained LDA topic model is proposed,which embeds semantic prior knowledge into the LDA model,and discovers the relevance between evaluation object and emotion words while effectively extracting them.Through experimental analysis,the CELDA model has a good effect on the extraction of evaluation object,emotion words and their associated relationships.