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首页> 外文期刊>Journal of Experimental and Theoretical Artificial Intelligence >Trust estimation of the semantic web using semantic webrnclustering
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Trust estimation of the semantic web using semantic webrnclustering

机译：使用语义编织的语义网信任度估计

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摘要

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.
机译：这些天来，语义网和社交网络的发展在互联网世界中不可否认。评估该领域的信任度，语义网的广泛性一直是非常具有挑战性的。近年来，已经进行了广泛的研究来估计语义网的信任度。由于语义网的信任度是一个多维问题，因此本文使用社交网络权限的参数，页面链接权限的值和语义权限来评估信任度。由于语义网络的空间大，我们考虑了语义子网簇的问题范围，获得了每个簇元素的信任度作为本地信任度，并根据外部资源的本地信任度和群集彼此之间的信任度计算了外部资源的信任度。根据实验结果，提出的方法显示Fscore超过79％，比Eigen，Tidal和集中式信任方法平均多11.9％。该方法的平均误差为12.936，比Eigen和Tidal信任方法平均低9.75％。

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