A classification approach for less popular webpages based on latent semantic analysis and rough set model

作者：

Highlights：

• We explore the classification of less popular webpages which have sparse tags.

• LSA extends information of sparse tags of less popular webpages.

• The proposed method refines them into hubs, bridges and attached webpages.

• Density-relation-based rough set model is built to classify attached webpages.

• Attached webpages are semantically classified with the increase of modularity.

摘要

•We explore the classification of less popular webpages which have sparse tags.•LSA extends information of sparse tags of less popular webpages.•The proposed method refines them into hubs, bridges and attached webpages.•Density-relation-based rough set model is built to classify attached webpages.•Attached webpages are semantically classified with the increase of modularity.

论文关键词：Webpage classification,Complex network analysis,Rough set,Latent semantic analysis

论文评审过程：Available online 19 August 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.08.013