Fuzzy Models for Link Prediction in Social Networks

Abstract

Predicting missing links and links that may occur in the future in social networks is an attention grabbing topic amid the social network analysts. Owing to the relationship between human‐based system and social sciences in this field, granular computing can help us to model the systems more effectively. The present study aims to propose two new similarity indices, based on granular computing approach and fuzzy logic. It also presents a new hybrid model for creating synergy between various link prediction models. Results show that fuzzy system analysis, in comparison with the crisp approach, can make more effective predictions through better expression of network characteristics. The indices are tested on collaboration networks. It is found that the accuracy of predictions is significantly higher than the crisp approach. It can modify the models for computing the strength of the links and/or predicting the evolutions of the social networks.

Link prediction in online social networks based on supervised joint denoising model

“…Symeonidis 等 [20] 采用谱聚类的方法对社 交网络的链接预测进行了研究; 他们通过降维的方法获得一个更小的矩阵, 采用该矩阵能够提高预测 效果; 他们不但计算了类内节点之间的相似度而且计算了不同类之间的节点相似度. Bastani 等 [21] 提 出模糊模型对社交网络链接预测进行研究, 他们基于粒计算和模糊逻辑提出了两种新的相似指数, 并 且基于多个链接预测模型提出了一个新的复合模型, 该模糊模型能够通过更好的网络特征表示来提高 链接预测精度. Bliss 等 [22] 提出一个基于领域相似性和节点相似性的线性组合模型, 并采用自适应协 方差矩阵进化策略对该模型权重进行优化, 该模型能够较好地进行链接预测.…”

Measuring fuzzy domination in fuzzy weighted directed social networks

“…The fuzzy relations help in modelling the strength of relations between the members. The membership degree µ(x, y) represents the strength of relationship betweenx and y, so the membership degree can be Fig.1.Representing relationship intensity and reliability associated with it [6] defined as [14] [16].…”

Optimizing Multiple Quality Responses in the Taguchi Method Using Fuzzy Goal Programming: Modeling and Applications

“…Hence, fuzzy GP (FGP) models can be used. [11][12][13][14] The FGP models are utilized in optimizing performance in a wide range of business applications. [15][16][17][18] In some industrial applications using designed experiments, process factor settings and product's quality responses are considered imprecise and can be expressed as intervals.…”

“…In practice, however, these values may be unknown. Hence, fuzzy GP (FGP) models can be used . The FGP models are utilized in optimizing performance in a wide range of business applications …”