Community detection in graphs

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Community detection in graphs

The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i.e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such clusters, ...

متن کامل

Community Detection on Evolving Graphs

Clustering is a fundamental step in many information-retrieval and data-mining applications. Detecting clusters in graphs is also a key tool for finding the community structure in social and behavioral networks. In many of these applications, the input graph evolves over time in a continual and decentralized manner, and, to maintain a good clustering, the clustering algorithm needs to repeatedl...

متن کامل

An Introduction to Community Detection in Graphs

In both society and nature, communities have always been ubiquitous as elementary forms of organization and have been also accepted intuitively as the niches and loci inside which humans (or possibly other living beings too) place and identify themselves according to various contextual, geographical, historical, cultural, political etc. conditions. Our aim here is to present an introductory and...

متن کامل

Active Community Detection in Massive Graphs

A canonical problem in graph mining is the detection of dense communities. This problem is exacerbated for a graph with a large order and size – the number of vertices and edges – as many community detection algorithms scale poorly. In this work we propose a novel framework for detecting active communities that consist of the most active vertices in massive graphs. The framework is applicable t...

متن کامل

Community detection in directed acyclic graphs

Some temporal networks, most notably citation networks, are naturally represented as directed acyclic graphs (DAGs). To detect communities in DAGs, we propose a modularity for DAGs by defining an appropriate null model (i.e., randomized network) respecting the order of nodes. We implement a spectral method to approximately maximize the proposed modularity measure and test the method on citation...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Physics Reports

سال: 2010

ISSN: 0370-1573

DOI: 10.1016/j.physrep.2009.11.002