We apply recent developments in data-mining and statistics, using affinity propagation (AP) to identify regional typologies the European Union (EU) characterize major factors between rural–r...

Subspace clustering is an eminent task to detect the clusters in subspaces. Density-based approaches assume the high-density region in the subspace as a cluster, but it creates density divergence problem. The proposed work improves the performance of Density Conscious subspace clustering (DENCOS) by utilizing the Affinity Propagation (AP) algorithm to detect the local densities for a dataset. I...

Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such "exemplars" can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only if that initial choice is close to a good solution. We devised a method called "affinity propagation," which ta...

Original scientific paper In view of the unsatisfying clustering effect of affinity propagation (AP) clustering algorithm when dealing with data sets of complex structures, an adaptive semi-supervised affinity propagation clustering algorithm based on structural similarity (SAAP-SS) is proposed in this paper. First, a novel structural similarity is proposed by solving a non-linear, low-rank rep...

Light field editing is a complex task, due to the large amount of data and the need to keep consistency between views. This has hampered the creation of efficient edit propagation methods, similar to those existing for single images. We propose a framework to edit light fields at interactive rates, by propagating some sparse user edits in the full light field. This propagation is guided by a no...

-Particle swarm optimization (PSO) is undoubtedly one of the most widely used swarm intelligence algorithm. Generally, each particle is assigned an initial value randomly. In this paper an improved PSO clustering algorithm based on affinity propagation (APPSO) is proposed which provides new ideas and methods for cluster analysis. Firstly the proposed algorithm get initial cluster centers by aff...

Clustering analysis aims to discover the underlying clusters in the data points according to their similarities. It has wide applications ranging from bioinformatics to astronomy. Here, we proposed a Generalized Affinity Propagation (G-AP) clustering algorithm. Data points are first organized in a sparsely connected in-tree (IT) structure by a physically inspired strategy. Then, additional edge...