基于主观倾向值和 EasyEnsemble 算法的 虚假评论识别方法.

In order to detect online spam reviews effectively, this paper proposed a method to detect spam reviews based on XGBoost-EasyEnsemble algorithm. Firstly, according to the characteristics of spam reviews, this paper proposed a calculation method of subjectivity and built a multi-dimensional feature model. Secondly, in view of the class-imbalance problem, EasyEn semble algorithm used integration strategy to make up for the defects of the under-sampling method, and fully utilized sample information. Finally, it chose XGBoost model with higher diversity and accuracy as base classifier to train. In terms of AUC. comparative experiments on reviews from Yelp. com was conducted with five hot machine learning algorithms, and the results verify the validity of the method. [ABSTRACT FROM AUTHOR]