Modeling an web community discovery method with web page attraction

Article type: Research Article

Authors: Lei, Shi^{; *}

Affiliations: College of Computer Science, Chengdu Normal University, Chengdu, China

Correspondence: [*] Corresponding author. Shi Lei, College of Computer Science, Chengdu Normal University, Chengdu, China. E-mail: 1172202434@qq.com.

Abstract: An improved Web community discovery algorithm is proposed in this paper based on the attraction between Web pages to effectively reduce the complexity of Web community discovery. The proposed algorithm treats each Web page in the Web pages collection as an individual with attraction based on the theory of universal gravitation, elaborates the discovery and evolution process of Web community from a Web page in the Web pages collection, defines the priority rules of Web community size and Web page similarity, and gives the calculation formula of the change in Web page similarity. Finally, an experimental platform is built to analyze the specific discovery process of the Web community in detail, and the changes in cumulative distribution of Web page similarity are discussed. The results show that the change in the similarity of a new page satisfies the power-law distribution, and the similarity of a new page is proportional to the size of Web community that the new page chooses to join.

Keywords: Web community, web page, attraction, evolution process, web page similarity

DOI: 10.3233/JIFS-202366

Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11159-11169, 2021