Trust estimation of the semantic web using semantic web clustering. Issue 3 (4th May 2017)

• Record Type: Journal Article
• Authors: Shirgahi, Hossein; Mohsenzadeh, Mehran; Haj Seyyed Javadi, Hamid
• Is Part Of: Journal of experimental & theoretical artificial intelligence. Volume 29:Issue 3(2017)
• Page Start: 537
• Page End: 556
• Publication Date: 2017-05-04
• Subjects: Trust estimation -- semantic web -- clustering -- social network; Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/0952813X.2016.1199601
• Languages: English
• ISSNs: 0952-813X

Abstract

Abstract: Development of semantic web and social network is undeniable in the Internet world these days. Widespread nature of semantic web has been very challenging to assess the trust in this field. In recent years, extensive researches have been done to estimate the trust of semantic web. Since trust of semantic web is a multidimensional problem, in this paper, we used parameters of social network authority, the value of pages links authority and semantic authority to assess the trust. Due to the large space of semantic network, we considered the problem scope to the clusters of semantic subnetworks and obtained the trust of each cluster elements as local and calculated the trust of outside resources according to their local trusts and trust of clusters to each other. According to the experimental result, the proposed method shows more than 79% Fscore that is about 11.9% in average more than Eigen, Tidal and centralised trust methods. Mean of error in this proposed method is 12.936, that is 9.75% in average less than Eigen and Tidal trust methods.