Apr 18, 2019 · It seeks to identify natural divisions that may exist in the input networks that partition the vertices into coherent modules (or communities).
Jan 15, 2020 · Community detection is a discovery tool used by network scientists to analyze the structure of real-world networks.
In this paper, we present a fast and efficient incremental approach toward dynamic community detection. The key con- tribution is a generic technique called ∆- ...
Abstract—Community detection is a discovery tool used by network scientists to analyze the structure of real-world net- works. It seeks to identify natural ...
This paper presents a fast and efficient incremental approach toward dynamic community detection using a generic technique called Δ-screening, ...
Community detection is a discovery tool used by network scientists to analyze the structure of real-world networks. It seeks to identify natural divisions ...
We present a fast and efficient incremental approach toward dynamic community detection. The key contribution is a generic technique called ∆-screening, which ...
People also ask
What are the different approaches to community detection?
Which algorithm is best for community detection?
Which is a fast local community detection algorithm in complex networks?
Community detection is a discovery tool used by network scientists to analyze the structure of real-world networks. It seeks to identify natural divisions ...
A Fast and Efficient Incremental Approach toward Dynamic Community Detection. 動的コミュニティ検出に向けた高速で効率的なインクリメンタルアプローチ【JST・京大 ...
Abstract—Detecting communities in time-evolving/dynamic networks is an important operation used in many real-world network science applications.