基于LDA模型的餐馆评论排序

摘要

In order to solve the problems of implicit aspects in review text and the inconsistency between rank of review and review text, this paper makes use of LDA on restaurant reviews to get the useful topics and discard unrelated ones, then gets the scores of some aspects based on them, and at last a model, which can predict ranks of restaurants based on new reviews, is trained with logistic regression using these scores. Experimental results show that the effectiveness of this method is better.%在餐馆评论中,存在评论文本未明确指出评价等级及评论文本不一致等问题.为此,提出一种基于LDA模型的餐馆评论排序方法.利用LDA模型对评论文本进行主题抽取,过滤掉不相关评论,基于过滤后的用户评论和用户给出的评论等级计算餐馆评论若干方面的得分,在该得分的基础上,利用逻辑回归进行训练,得到餐馆评论排序模型.实验结果表明,该方法的排序效果较优.