BACKGROUND In the era of semantic web, life science ontologies play an important role in tasks such as annotating biological objects, linking relevant data pieces, and verifying data consistency. Understanding ontology structures and overlapping ontologies is essential for tasks such as ontology reuse and development. We present an exploratory study where we examine structure and look for patte...

Most complex networks demonstrate a significant property ‘community structure’, meaning that the network nodes are often joined together in tightly knit groups or communities, while there are only looser connections between them. Detecting these groups is of great importance and has immediate applications, especially in the popular online social networks like Facebook and Twitter. Many of these...

Overlapping community detection is a popular topic in complex networks. As compared to disjoint community structure, overlapping community structure is more suitable to describe networks at a macroscopic level. Overlaps shared by communities play an important role in combining different communities. In this paper, two methods are proposed to detect overlapping community structure. One is called...

In this paper we study the topology effects on diffusion process in signed networks. Considering a simple threshold model for diffusion process, it is extended to signed networks and some appropriate definitions are proposed. This model is a basic model that could be extended and applied in analyzing dynamics of many real phenomena such as opinion forming or innovation diffusion in social netwo...

Discovering overlapping community structures is a crucial step to understanding the structure and dynamics of many networks. In this paper we develop a symmetric binary matrix factorization model to identify overlapping communities. Our model allows us not only to assign community memberships explicitly to nodes, but also to distinguish outliers from overlapping nodes. In addition, we propose a...

Community structure can be observed in many natural, biological and social networks. Studies suggest that these communities may have organized in a hierarchical manner while some communities overlap with others. This paper introduces an algorithm to detect such hierarchical and overlapping community structures in networks based on the concept of maximal cliques. It introduces an alternate modul...

This article is about community detection algorithms in graphs. First a new method will be introduced, which is based on an extension [16] of the commonly used modularity [17, 18, 19, 20] and gives overlapping communities. We list and compare the results given by our new method and some other algorithms yileding either overlapping or non-overlapping communities. While the main use of the propos...

We introduce a game-theoretic framework to address the community detection problem based on the social networks’ structure. The dynamics of community formation is framed as a strategic game called community formation game: Given a social network, each node is selfish and selects communities to join or leave based on her own utility measurement. A community structure can be interpreted as an equ...

This paper presents a novel spectral algorithm with additive clustering, designed to identify overlapping communities in networks. The algorithm is based on geometric properties of the spectrum of the expected adjacency matrix in a random graph model that we call stochastic blockmodel with overlap (SBMO). An adaptive version of the algorithm, that does not require the knowledge of the number of...

A lot of complex systems in nature and society can be represented as the form of network. The small-scale subnets topological features are vital to understand the dynamics and function of the networks. Triangles comprised of three nodes are the simplest subnet in the network. Based on the triangle distribution of the complex network, we present a novel approach to detect overlapping community s...