Hypergraph Clustering Based on PageRank (KDD, 2020) [paper] Dual Channel Hypergraph Collaborative Filtering (KDD, 2020) [paper] Hypergraph Convolutional Recurrent Neural Network (KDD, 2020) [paper] E-tail Produc
Hypergraph Clustering Based on PageRank (KDD, 2020) [paper] Dual Channel Hypergraph Collaborative Filtering (KDD, 2020) [paper] Hypergraph Convolutional Recurrent Neural Network (KDD, 2020) [paper] E-tail Product Return Prediction via Hypergraph-based Local Graph Cut (KDD, 2018) [paper] ...
related sets of diseases; (i) cancer, lymphoma and leukaemia and metastatic cancer, (ii) diabetes and diabetes with complication and (iii) mild and severe liver disease which were combined into three single conditions as they are by their nature closely related and would induce pseudoclustering....
Tran studies protein function prediction building a graph from a similarity matrix derived from gene expression data [20] and then applying soft clustering to this graph to produce a hypergraph. Function prediction using this hyper- graph is then shown to be superior to predictions based on graphs...
High-order s-walks (s > 1) are possi- ble on hypergraphs whereas for graphs, all walks are 1-walks. The hypergraph walk-based methods we develop include connected component analyses, graph-distance based met- rics such as closeness-centrality, and motif-based measures such as clustering ...