Computer Engineering Commons^™

A New Network-Based Community Detection Algorithm For Disjoint Communities, Peli̇n Çeti̇n, Şahi̇n Emrah Amrahov

Turkish Journal of Electrical Engineering and Computer Sciences

A community is a group of people that shares something in common. The definition of the community can be generalized as things that have common properties. By using this definition, community detection can be used to solve different problems in various areas. In this study, we propose a new network-based community detection algorithm that can work on different types of datasets. The proposed algorithm works on unweighted graphs and determines the weight by using cosine similarity. We apply a bottom-up approach and find the disjoint communities. First, we accept each node as an independent community. Then, the merging process is …

Community Detection Algorithm In Multi-Relational Networks, Jingping Yu, Zheng Jie, Guixiang Zhu

Journal of System Simulation

Abstract: In view of the traditional community detection algorithms being mainly applied to single relational networks, ignoring the interaction of relationship in the multi-relational networks, being unable to distinguish the importance of each relation for community detection, a novel algorithm called InteractRank was proposed. Based on the node and the relation of ranking model, the algorithm could transform multi-relational network into single relational network. Combined the PageRank algorithm and the random walk model, the algorithm considered the connection within groups and between groups in multi-relational networks. After transforming into single relational networks, spectral clustering algorithm was adopted to detect community. …

Hierarchical Agglomerative Community Detection Algorithm Based On Similarity Modularity, Wenwei Zhan, Jingke Xi, Zhixiao Wang

Journal of System Simulation

Abstract: Fast Unfolding is a hierarchical community detection algorithm based on modularity. It runs very fast, but the accuracy needs to be improved. Because the algorithm adopts traditional modularity to merger communities, it only considers node link information and ignores the neighbor nodes. Therefore, two nodes that have common neighbors and weak link information may not be merged, thus affecting the accuracy. In view of the shortcomings, a hierarchical agglomerative community detection algorithm based on similarity modularity was proposed through introducing optimized similarity to improve the modularity. It adopts NMI as the accuracy measurement. Experiments on the real network …

Community Detection In Complex Networks Using A New Agglomerative Approach, Majid Arasteh, Somayeh Alizadeh

Turkish Journal of Electrical Engineering and Computer Sciences

Complex networks are used for the representation of complex systems such as social networks. Graph analysis comprises various tools such as community detection algorithms to uncover hidden data. Community detection aims to detect similar subgroups of networks that have tight interconnections with each other while, there is a sparse connection among different subgroups. In this paper, a greedy and agglomerative approach is proposed to detect communities. The proposed method is fast and often detects high-quality communities. The suggested method has several steps. In the first step, each node is assigned to a separated community. In the second step, a vertex …

Resolving Namesakes Using The Author's Social Network, Ijaz Hussain, Sohail Asghar

Turkish Journal of Electrical Engineering and Computer Sciences

Author name ambiguity may occur when multiple authors share the same name or different name variations of a single author exist. This degrades search results and correct attributions in bibliographic databases. Existing solutions require either the actual number of ambiguous authors or extra information that is collected from the Web. However, in many scenarios, obtaining such auxiliary information is not possible or requires much extra effort. An effective and scalable method, ASONET, is proposed that uses graph community detection algorithms and graph operations to disambiguate namesakes. The citation dataset is preprocessed and ambiguous author blocks are formed. A graph structural …

A Faster Version Of Louvain Method For Community Detection For Efficient Modeling And Analytics Of Cyber Systems, Sunanda Vivek Shanbhaq

Open Access Theses

Cyber networks are complex networks with various hosts forming the entities of the network and the communication between them forming the edges of the network. Most cyber networks exhibit a community structure. A community is a group of nodes that are densely connected with each other as compared to other nodes in the network. Representing an IP network in the form of communities helps in viewing the network from different levels of granularity and makes the visualization of the network cleaner and more pleasing to the eye. This will help significantly in cyber attack detection in large scale cyber networks. …

Using Power-Law Properties Of Social Groups For Cloud Defense And Community Detection, Justin L. Rice

Doctoral Dissertations

The power-law distribution can be used to describe various aspects of social group behavior. For mussels, sociobiological research has shown that the Lévy walk best describes their self-organizing movement strategy. A mussel's step length is drawn from a power-law distribution, and its direction is drawn from a uniform distribution. In the area of social networks, theories such as preferential attachment seek to explain why the degree distribution tends to be scale-free. The aim of this dissertation is to glean insight from these works to help solve problems in two domains: cloud computing systems and community detection.

Privacy and security are …