A Web Page Clustering Method Based on Formal Concept Analysis

被引：5
|
作者：
Zhang, Zuping [1 ]
Zhao, Jing [1 ]
Yan, Xiping [1 ]
机构：
[1] Cent S Univ, Sch Informat Sci & Engn, Changsha 410000, Hunan, Peoples R China
来源：
INFORMATION | 2018年 / 9卷 / 09期
基金：
中国国家自然科学基金;
关键词：
formal concept analysis; feature weight; cross linked list; concept lattice; Web page clustering;
D O I：
10.3390/info9090228
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Web page clustering is an important technology for sorting network resources. By extraction and clustering based on the similarity of the Web page, a large amount of information on a Web page can be organized effectively. In this paper, after describing the extraction of Web feature words, calculation methods for the weighting of feature words are studied deeply. Taking Web pages as objects and Web feature words as attributes, a formal context is constructed for using formal concept analysis. An algorithm for constructing a concept lattice based on cross data links was proposed and was successfully applied. This method can be used to cluster the Web pages using the concept lattice hierarchy. Experimental results indicate that the proposed algorithm is better than previous competitors with regard to time consumption and the clustering effect.
引用
收藏
页数：14
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