Fast extraction of the backbone of projected bipartite networks to aid community detection
نویسندگان
چکیده
This paper introduces a computationally inexpensive method of extracting the backbone of one-mode networks projected from bipartite networks. We show that the edge weights in one-mode projections are distributed according to a Poisson binomial distribution. Finding the expected weight distribution of a one-mode network projected from a random bipartite network only requires knowledge of the bipartite degree distributions. Being able to extract the backbone of a projection proves to be highly beneficial to filter out redundant information in large complex networks and to narrow down the information in the one-mode projection to the most relevant. We further demonstrate that the backbone of a one-mode projection aids in the detection of communities.
منابع مشابه
Designing an Ontology for Knowledge Discovery in Iran’s Vaccine
Ontology is a requirement engineering product and the key to knowledge discovery. It includes the terminology to describe a set of facts, assumptions, and relations with which the detailed meanings of vocabularies among communities can be determined. This is a qualitative content analysis research. This study has made use of ontology for the first time to discover the knowledge of vaccine in Ir...
متن کاملA Fast Approach to the Detection of All-Purpose Hubs in Complex Networks with Chemical Applications
A novel algorithm for the fast detection of hubs in chemical networks is presented. The algorithm identifies a set of nodes in the network as most significant, aimed to be the most effective points of distribution for fast, widespread coverage throughout the system. We show that our hubs have in general greater closeness centrality and betweenness centrality than vertices with maximal degree, w...
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 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 کاملThe backbone of bipartite projections: Inferring relationships from co-authorship, co-sponsorship, co-attendance and other co-behaviors
The analysis and visualization of weighted networks pose many challenges, which have led to the development of techniques for extracting the network’s backbone, a subgraph composed of only the most significant edges. Weighted edges are particularly common in bipartite projections (e.g. networks of coauthorship, co-attendance, co-sponsorship), which are often used as proxies for one-mode network...
متن کامل