Results 31 to 40 of about 10,205 (230)

Prediction of Graduation Development Based on Hypergraph Contrastive Learning With Imbalanced Sampling

IEEE Access, 2023
With the increasingly competitive job market, the employment issue for college graduates has received more and more attention. Predicting graduation development can help students understand their suitable graduation development, thus easing the pressure ...
Yong Ouyang, Tuo Feng, Rong Gao, Yubin Xu, Jinghang Liu   +4 more
doaj   +1 more source

Almost Self-Complementary Uniform Hypergraphs

Discussiones Mathematicae Graph Theory, 2018
A k-uniform hypergraph (k-hypergraph) is almost self-complementary if it is isomorphic with its complement in the complete k-uniform hypergraph minus one edge. We prove that an almost self-complementary k-hypergraph of order n exists if and only if (nk)$\
Wojda Adam Paweł
doaj   +1 more source

Exploring complex and heterogeneous correlations on hypergraph for the prediction of drug-target interactions

, 2021
The continuous emergence of drug-target interaction data provides an opportunity to construct a biological network for systematically discovering unknown interactions.
Yan, C, Dai, Q, Gao, Y, Ji, S, Zou, C, Zhao, X, Yang, Y, Zhu, J, Ruan, D   +8 more
core   +1 more source

Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan. [PDF]

PLoS Computational Biology, 2016
Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority
Elizabeth N Davison, Benjamin O Turner, Kimberly J Schlesinger, Michael B Miller, Scott T Grafton, Danielle S Bassett, Jean M Carlson   +6 more
doaj   +1 more source

Hypergraph categories

Journal of Pure and Applied Algebra, 2019
38 ...
Brendan Fong, David I. Spivak
openaire   +4 more sources

Hypernetwork science via high-order hypergraph walks

EPJ Data Science, 2020
We propose high-order hypergraph walks as a framework to generalize graph-based network science techniques to hypergraphs. Edge incidence in hypergraphs is quantitative, yielding hypergraph walks with both length and width.
Sinan G. Aksoy, Cliff Joslyn, Carlos Ortiz Marrero, Brenda Praggastis, Emilie Purvine   +4 more
doaj   +1 more source

Tiling multipartite hypergraphs in quasi-random hypergraphs

Journal of Combinatorial Theory, Series B, 2023
22 pages.
Laihao Ding, Jie Han 0002, Shumin Sun, Guanghui Wang 0002, Wenling Zhou   +4 more
openaire   +3 more sources

Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation

, 2021
Social relations are often used to improve recommendation quality when user-item interaction data is sparse in recommender systems. Most existing social recommendation models exploit pairwise relations to mine potential user preferences.
Zhang, Xiangliang, Junliang Yu, Li, Jundong, Hongzhi Yin, Jundong Li, Nguyen Quoc Viet Hung, Hung, Nguyen Quoc Viet, Wang, Qinyong, Qinyong Wang, Yu, Junliang, Nguyen, Quoc Viet Hung, Yin, Hongzhi, Xiangliang Zhang   +12 more
core   +1 more source

MSHC: a multi-stage hypergraph clustering algorithm

Shenzhen Daxue xuebao. Ligong ban
As a high-dimensional extension of ordinary graphs, hypergraphs can more flexibly reflect high-order complex relationships between nodes. Hypergraph clustering aims to discover complex high-order correlations in powerful hypergraph structures.
ZHANG Chunying, WANG Jing, LIU Lu, LAN Siwu, ZHANG Qingda   +4 more
doaj   +1 more source

Lagrangians of Hypergraphs [PDF]

Combinatorics, Probability and Computing, 2002
How large can the Lagrangian of an r-graph with m edges be? Frankl and Füredi [1] conjectured that the r-graph of size m formed by taking the first m sets in the colex ordering of N(r) has the largest Lagrangian of all r-graphs of size m. We prove the first ‘interesting’ case of this conjecture, namely that the 3-graph with (t3) edges and ...
openaire   +2 more sources