Seeding then expanding is a commonly used scheme to discover overlapping communities from a network. Most seeding methods existed are either too complexity to scale to large networks or too simple to select high-quality seeds; and the non-principled functions used by most expanding methods lead the poor performances when applied them on diverse networks. This paper proposes a new method which t...

In this paper, we develop the idea to partition the edges of a graph in order to uncover overlapping communities of its nodes. Our approach is based on the construction of different types of weighted line graphs, i.e. graphs whose nodes are the links of the original graph, that encapsulate differently the relations between the edges. Weighted line graphs are argued to provide an alternative, va...

Nowadays, people use online social networks almost every day. They activate either due to their interests, or to search or catch their desirable information. Users of online social networks generate structural and contextual traces that can be analyzed by, i.e., network science researchers. Researchers can describe networks fabricated out of online traces from different perspectives that one of...

We show that a complex network of phase oscillators may display interfaces between domains (clusters) of synchronized oscillations. The emergence and dynamics of these interfaces are studied for graphs composed of either dynamical domains (influenced by different forcing processes), or structural domains (modular networks). The obtained results allow us to give a functional definition of overla...

In this paper, we develop the idea to partition the edges of a weighted graph in order to uncover overlapping communities of its nodes. Our approach is based on the construction of different types of weighted line graphs, i.e. graphs whose nodes are the links of the original graph, that encapsulate differently the relations between the edges. Weighted line graphs are argued to provide an altern...

We present a fast tensor-based approach for detecting hidden overlapping communities under the mixed membership stochastic block (MMSB) model. We present two implementations, viz., a GPU-based implementation which exploits the parallelism of SIMD architectures and a CPU-based implementation for larger datasets, where the GPU memory does not suffice. Our GPU-based implementation involves a caref...

We introduce an intuitive model that describes both the emergence of community structure and the evolution of the internal structure of communities in growing social networks. The model comprises two complementary mechanisms: One mechanism accounts for the evolution of the internal link structure of a single community, and the second mechanism coordinates the growth of multiple overlapping comm...

Automatic detection and segmentation of overlapping leaves in dense foliage can be a difficult task, particularly for leaves with strong textures and high occlusions. We present Dense-Leaves, an image dataset with ground truth segmentation labels that can be used to train and quantify algorithms for leaf segmentation in the wild. We also propose a pyramid convolutional neural network with multi...

This paper reports on our ongoing work regarding opinion mining from Web-based discussion forums in the realm of the Understanding Advertising (UAd) project. Our approach to opinion mining is to first RDFise discussion forums in SIOC, and in a second phase to interlink the so created data with linked datasets such as DBpedia. We are confident that this should allow a market researcher to formul...

Breast tissue segmentation into dense and fat tissue is important for determining the breast density in mammograms. Knowing the breast density is important both in diagnostic and computer-aided detection applications. There are many different ways to express the density of a breast and good quality segmentation should provide the possibility to perform accurate classification no matter which cl...