Network alignment
Complex networks are frequently employed to model physical or virtual complex systems.
When certain entities exist across multiple systems simultaneously, unveiling their …
When certain entities exist across multiple systems simultaneously, unveiling their …
Deep graph matching consensus
This work presents a two-stage neural architecture for learning and refining structural
correspondences between graphs. First, we use localized node embeddings computed by a …
correspondences between graphs. First, we use localized node embeddings computed by a …
PageRank beyond the web
Google's PageRank method was developed to evaluate the importance of web-pages via
their link structure. The mathematics of PageRank, however, are entirely general and apply …
their link structure. The mathematics of PageRank, however, are entirely general and apply …
[PDF][PDF] Predict anchor links across social networks via an embedding approach.
Predicting anchor links across social networks has important implications to an array of
applications, including cross-network information diffusion and cross-domain …
applications, including cross-network information diffusion and cross-domain …
Final: Fast attributed network alignment
Multiple networks naturally appear in numerous high-impact applications. Network
alignment (ie, finding the node correspondence across different networks) is often the very …
alignment (ie, finding the node correspondence across different networks) is often the very …
[HTML][HTML] A review of protein–protein interaction network alignment: From pathway comparison to global alignment
Network alignment provides a comprehensive way to discover the similar parts between
molecular systems of different species based on topological and biological similarity. With …
molecular systems of different species based on topological and biological similarity. With …
Adaptive network alignment with unsupervised and multi-order convolutional networks
Network alignment is the problem of pairing nodes between two graphs such that the paired
nodes are structurally and semantically similar. A well-known application of network …
nodes are structurally and semantically similar. A well-known application of network …
Entity alignment for knowledge graphs with multi-order convolutional networks
Knowledge graphs (KGs) have become popular structures for unifying real-world entities by
modelling the relationships between them and their attributes. To support multilingual …
modelling the relationships between them and their attributes. To support multilingual …
A comparative study on network alignment techniques
Network alignment is a method to align nodes that belong to the same entity from different
networks. A well-known application of network alignment is to map user accounts from …
networks. A well-known application of network alignment is to map user accounts from …
Community-enhanced de-anonymization of online social networks
Online social network providers have become treasure troves of information for marketers
and researchers. To profit from their data while honoring the privacy of their customers …
and researchers. To profit from their data while honoring the privacy of their customers …