Papers Local Community Detection

Pre-trained Prompt-driven Semi-supervised Local Community Detection

Semi-supervised local community detection aims to leverage known communities to detect the community containing a given node. Although existing semi-supervised local community detection studies yield promising results, t…

LGDE: Local Graph-based Dictionary Expansion

We present Local Graph-based Dictionary Expansion (LGDE), a method for data-driven discovery of the semantic neighbourhood of words using tools from manifold learning and network science. At the heart of LGDE lies the cr…

Random Walk on Multiple Networks

Random Walk is a basic algorithm to explore the structure of networks, which can be used in many tasks, such as local community detection and network embedding. Existing random walk methods are based on single networks t…

Uncovering the Local Hidden Community Structure in Social Networks

Hidden community is a useful concept proposed recently for social network analysis. To handle the rapid growth of network scale, in this work, we explore the detection of hidden communities from the local perspective, an…

LoCEC: Local Community-based Edge Classification in Large Online Social Networks

Relationships in online social networks often imply social connections in the real world. An accurate understanding of relationship types benefits many applications, e.g. social advertising and recommendation. Some recen…

Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection

Community structure is ubiquitous in real-world complex networks. The task of community detection over these networks is of paramount importance in a variety of applications. Recently, nonnegative matrix factorization (N…

Generative models for local network community detection

Local network community detection aims to find a single community in a large network, while inspecting only a small part of that network around a given seed node. This is much cheaper than finding all communities in a ne…

Local Network Community Detection with Continuous Optimization of Conductance and Weighted Kernel K-Means

Local network community detection is the task of finding a single community of nodes concentrated around few given seed nodes in a localized way. Conductance is a popular objective function used in many algorithms for lo…

A Graph-Based Analysis of Medical Queries of a Swedish Health Care Portal