… with the representation of relationships in a social network [41]. Therefore, we adopt one
type of social network, namely the trust network, in which users explicitly express their views on …

… The TCop-Kmeans algorithm enhances traditional K-means … TCop-Kmeans algorithm with
traditional K-means algorithms … TCop-Kmeans algorithm and traditional K-means algorithms. …

… into the opinion dynamics in social networks. Recent … K-means objective function value
during each stage t (see Theorem 2); moreover, our approach can always generate a finite COP …

… In this study, trust constraints are used to guide the traditional Cop-Kmeans algorithm,
and thus TCop-Kmeans algorithm is produced, as presented below (labeled as Algorithm 1). …

… This paper presented a clustering method based on boosting principle to find the circles of
the social networks. The boosting framework is used with modified COP K-means method that …

… This book focuses on the following three key topics in social network large-scale decision-…
Then, two clustering algorithms are put forward, including trust Cop-K-means clustering …

… In k-means algorithm, the selection of initial clustering centers has a strong influence on the
clustering result. In SL T model, social networks data is incorporated into k-means … Thus, Cop-…

… than 20) with different views jointly negotiate and earn a consensus in a social network [5]. …
as community detection algorithm [6] and trust cop-Kmeans clustering algorithm [5]. CRP aims …

… ] designed a trust Cop-K means algorithm that used prior knowledge about the trust
relationships of DMs. The fusion of two measurement attributes provides a new solution for …

… A popular approach to cluster centroid calculation, used in k-means clustering, is to calculate
… DB and COP performed well in the presence of cluster overlap. With real data, D and COP …