157 citations · 314 across the 13 of their papers we have counts for
6 papers · 1 filter
A similarity-based community detection method with multiple prototype representation
Kuang Zhou, Arnaud Martin, Quan Pan
Communities are of great importance for understanding graph structures in social networks. Some existing community detection algorithms use a single prototype to represent each gro…
Evidential relational clustering using medoids
Kuang Zhou, Arnaud Martin, Quan Pan +1
In real clustering applications, proximity data, in which only pairwise similarities or dissimilarities are known, is more general than object data, in which each pattern is descri…
Belief Hierarchical Clustering
Wiem Maalel, Kuang Zhou, Arnaud Martin +1
In the data mining field many clustering methods have been proposed, yet standard versions do not take into account uncertain databases. This paper deals with a new approach to clu…
Evidential Communities for Complex Networks
Kuang Zhou, Arnaud Martin, Quan Pan
Community detection is of great importance for understand-ing graph structure in social networks. The communities in real-world networks are often overlapped, i.e. some nodes may b…
Median evidential c-means algorithm and its application to community detection
Kuang Zhou, Arnaud Martin, Quan Pan +1
Median clustering is of great value for partitioning relational data. In this paper, a new prototype-based clustering method, called Median Evidential C-Means (MECM), which is an e…
Evidential-EM Algorithm Applied to Progressively Censored Observations
Kuang Zhou, Arnaud Martin, Quan Pan
Evidential-EM (E2M) algorithm is an effective approach for computing maximum likelihood estimations under finite mixture models, especially when there is uncertain information abou…