Community Detection in Censored Hypergraph

On the Minimax Misclassification Ratio of Hypergraph Community Detection

In this paper, community detection in hypergraphs is explored. Under a generative hypergraph model called “d-wise hypergraph stochastic block model” (d-hSBM) which naturally extends the Stochastic Block Model (SBM) from graphs to d-uniform hypergraphs, the asymptotic minimax mismatch ratio (the risk function in the community detection problem) is characterized. For proving the achievability, we...

Overlapping 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...

Contextual Hypergraph Modelling for Salient Object Detection

Salient object detection aims to locate objects that capture human attention within images. Previous approaches often pose this as a problem of image contrast analysis. In this work, we model an image as a hypergraph that utilizes a set of hyperedges to capture the contextual properties of image pixels or regions. As a result, the problem of salient object detection becomes one of finding salie...

Intrusion Detection with Hypergraph-Based Attack Models

Topic Detection with Hypergraph Partition Algorithm

An algorithm named SMHP (Similarity Matrix based Hypergraph Partition) algorithm is proposed, which aims at improving the efficiency of Topic Detection. In SMHP, a T-MI-TFIDF model is designed by introducing Mutual Information (MI) and enhancing the weight of terms in the title. Then Vector Space Model (VSM) is constructed according to terms' weight, and the dimension is reduced by combining H-...