Communities are not static; they evolve, split and merge, appear and disappear, i.e., they are the product of dynamical processes that govern the evolution of a network. A good algorithm for community detection should not only quantify the topology of the network but incorporate the dynamical processes that take place on the network. We present an algorithm for community detection that combines...

A wide variety of natural or artificial systems can be modeled as time-varying or temporal networks. To understand the structural and functional properties of these time-varying networked systems, it is desirable to detect and analyze the evolving community structure. In temporal networks, the identified communities should reflect the current snapshot network, and at the same time be similar to...

Local overlapping community detection is a hot problem in the field of studying complex networks. It process finding dense clusters based on local network information. This paper proposes method called greedy extended dynamic (GLOD) to address challenges detecting high-quality communities The goal improve accuracy by considering nature boundaries and leveraging GLOD consists several steps. Firs...

A fast community detection algorithm based on a q-state Potts model is presented. Communities (groups of densely interconnected nodes that are only loosely connected to the rest of the network) are found to coincide with the domains of equal spin value in the minima of a modified Potts spin glass Hamiltonian. Comparing global and local minima of the Hamiltonian allows for the detection of overl...

Community (also known as clusters) is a group of nodes with dense connection. Detecting outlier-communities from database is a big desire. In this paper we propose a novel Minimum Spanning Tree based algorithm for detecting outlier-communities from complex networks. The algorithm uses a new community validation criterion based on the geometric property of data partition of the data set in order...

‎‎‎in this paper‎, ‎the‎ notion of injectivity with respect to order dense embeddings in ‎‎the category of $s$-posets‎, ‎posets with a monotone action of a‎ pomonoid $s$ on them‎, ‎is studied‎. ‎we give a criterion‎, ‎like the baer condition for injectivity of modules‎, ‎or skornjakov criterion for injectivity of $s$-sets‎, ‎for the order dense injectivity‎. ‎also‎, ‎we consider such injectivit...

Identifying overlapping communities in networks is a challenging task. In this work we present a novel approach to community detection that utilizes the Bayesian non-negative matrix factorization (NMF) model to extract overlapping modules from a network. The scheme has the advantage of computational efficiency, soft community membership and an intuitive foundation. We present the performance of...

XML has been the de facto standard for digital editions for years, but its serious limitations include an inability to represent overlapping markup and the encoding of multiple annotation hierarchies. With emerging graph database technologies we have the opportunity to develop new approaches. In this paper the advantages and modelling principles of graph-based digital editions will be discussed.

Identifying overlapping communities in networks is a challenging task. In this work we present a probabilistic approach to community detection that utilizes a Bayesian non-negative matrix factorization model to extract overlapping modules from a network. The scheme has the advantage of soft-partitioning solutions, assignment of node participation scores to modules, and an intuitive foundation. ...

Detection of overlapping communities in complex networks has motivated recent research in the relevant fields. Aiming this problem, we propose a Markov dynamics based algorithm, called UEOC, which means, “unfold and extract overlapping communities”. In UEOC, when identifying each natural community that overlaps, a Markov random walk method combined with a constraint strategy, which is based on ...