Web spam classification method based on deep belief networks

作者：

Highlights：

• DBN- based classification model is proposed in this paper for web spam detection.

• SMOTE and DAE algorithms is applied in DBN to improve the classification performance

• The content and link feature is combined.

• The results obtained in this paper is better than the existing systems.

摘要

•DBN- based classification model is proposed in this paper for web spam detection.•SMOTE and DAE algorithms is applied in DBN to improve the classification performance•The content and link feature is combined.•The results obtained in this paper is better than the existing systems.

论文关键词：Web spam,Web spam classification,SMOTE,Deep learning,DAE,DBN

论文评审过程：Received 6 April 2017, Revised 6 December 2017, Accepted 7 December 2017, Available online 7 December 2017, Version of Record 22 December 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.12.016