Parameterized Correlation Clustering in Hypergraphs and Bipartite Graphs (KDD, 2020) [paper] 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 Pr...
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] ...
Long-form document matching is an important direction in the field of natural language processing and can be applied to tasks such as news recommendation and text clustering. However, long-form document matching suffers from noisiness an... Y Cheng,R Chen,X Yuan,... - 《Journal of Physics ...
Hypergraphs offer a framework to overcome such difficulties; biological networks can be intuitively described using the hypergraph model21. Klamtet al. and Mithaniet al. proposed using a hypergraph to represent biological networks21,22. Michoelet al. have used hypergraph-based spectral clustering to p...
2024. Available online: https://openreview.net/forum?id=XuNkuoihgG (accessed on 17 October 2024). Takai, Y.; Miyauchi, A.; Ikeda, M.; Yoshida, Y. Hypergraph clustering based on pagerank. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,...
Gdroid [12] first constructed a heterogeneous graph between APKs and APIs, and then obtained the neighborhood relationships between APIs using word2vec and clustering algorithms [13]. Then, they combined graph convolutional neural networks (GCN) to learn the representations of the APKs. And the ...