The paper presents an intelligent approach for the comparison of social networks through a cone model by using the fuzzy k-medoids clustering method. It makes use of a geometrical three-dimensional conical model, which astutely represents the user experience views. It uses both the static as well as the dynamic parameters of social networks. In this, we propose an algorithm that investigates which social network is more fruitful. For the experimental results, the proposed work is employed on the data collected from students from different universities through the Google forms, where students are required to rate their experience of using different social networks on different scales.

本文提出了一种利用模糊k-medoids聚类方法通过锥模型进行社交网络比较的智能方法。它利用了一个几何三维圆锥模型，该模型敏锐地代表了用户体验视图。它使用社交网络的静态和动态参数。在本文中，我们提出了一种算法，该算法研究哪个社交网络更富有成效。对于实验结果，将拟议的工作用于通过Google表单从不同大学的学生那里收集的数据，要求学生对他们使用不同规模的不同社交网络的经验进行评分。