Quantitative function for community detection.
نویسندگان
چکیده
We propose a quantitative function for community partition -- i.e., modularity density or D value. We demonstrate that this quantitative function is superior to the widely used modularity Q and also prove its equivalence with the objective function of the kernel k means. Both theoretical and numerical results show that optimizing the new criterion not only can resolve detailed modules that existing approaches cannot achieve, but also can correctly identify the number of communities.
منابع مشابه
Quantitative Function and Algorithm for Community Detection in Bipartite Networks
Community detection in complex networks is a topic of high interest in many fields. Bipartite networks are a special type of complex networks in which nodes are decomposed into two disjoint sets, and only nodes between the two sets can be connected. Bipartite networks represent diverse interaction patterns in many real-world systems, such as predator-prey networks, plant-pollinator networks, an...
متن کاملA Multiagent Reinforcement Learning algorithm to solve the Community Detection Problem
Community detection is a challenging optimization problem that consists of searching for communities that belong to a network under the assumption that the nodes of the same community share properties that enable the detection of new characteristics or functional relationships in the network. Although there are many algorithms developed for community detection, most of them are unsuitable when ...
متن کاملOverlapping Community Detection in Social Networks Based on Stochastic Simulation
Community detection is a task of fundamental importance in social network analysis. Community structures enable us to discover the hidden interactions among the network entities and summarize the network information that can be applied in many applied domains such as bioinformatics, finance, e-commerce and forensic science. There exist a variety of methods for community detection based on diffe...
متن کاملAn Optimized Firefly Algorithm based on Cellular Learning Automata for Community Detection in Social Networks
The structure of the community is one of the important features of social networks. A community is a sub graph which nodes have a lot of connections to nodes of inside the community and have very few connections to nodes of outside the community. The objective of community detection is to separate groups or communities that are linked more closely. In fact, community detection is the clustering...
متن کاملComparative Study on A Class of Evaluation Indices for Community Detection
Community detection and network partition are fundamental for uncovering the links between structure and function in complex networks. Recently Li et al. [11] introduced a novel quantitative function(D-value) for community detection which can overcome some drawbacks of the widely used modularity Q. We notice that although the modularity density Dλ has gained good performance for some networks, ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Physical review. E, Statistical, nonlinear, and soft matter physics
دوره 77 3 Pt 2 شماره
صفحات -
تاریخ انتشار 2008