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Found 5 papers, 0 papers with code
MUSE: Multi-faceted Attention for Signed Network Embedding
Signed network embedding is an approach to learn low-dimensional representations of nodes in signed networks with both positive and negative links, which facilitates downstream tasks such as link prediction with general data mining frameworks.
Hypernetwork Dismantling via Deep Reinforcement Learning
Network dismantling aims to degrade the connectivity of a network by removing an optimal set of nodes.
Heterogeneous Information Network-based Interest Composition with Graph Neural Network for Recommendation
Then, users' interests in each item from each pair of related meta-paths are calculated by a combination of the user and item representations.
HyperCI: A Higher Order Collective Influence Measure for Hypernetwork Dismantling
However, conventional network dismantling approaches focus on simple network which models only pairwise interaction between nodes while groupwise interactions among arbitrary number of nodes are ubiquitous in networked systems like integrated circuits.
Social and Information Networks Physics and Society
Session-based Social and Dependency-aware Software Recommendation
With the increase of complexity of modern software, social collaborative coding and reuse of open source software packages become more and more popular, which thus greatly enhances the development efficiency and software quality.
