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gat2vec: representation learning for attributed graphs
Network representation learning (NRL) enables the application of machine learning tasks
such as classification, prediction and recommendation to networks. Apart from their graph …
such as classification, prediction and recommendation to networks. Apart from their graph …
Sentiment analysis using lexico-semantic features
Sentiment analysis of the text deals with the mining of the opinions of people from their
written communication. With the increasing usage of online social media platforms for user …
written communication. With the increasing usage of online social media platforms for user …
Semi-supervised heterogeneous information network embedding for node classification using 1d-cnn
Network Representation Learning (NRL) is a method to learn a representation of a graph in
a low-dimensional space, such that the representation can be later utilized easily in various …
a low-dimensional space, such that the representation can be later utilized easily in various …
Graph neighborhood attentive pooling
Network representation learning (NRL) is a powerful technique for learning low-dimensional
vector representation of high-dimensional and sparse graphs. Most studies explore the …
vector representation of high-dimensional and sparse graphs. Most studies explore the …
REFINE: representation learning from diffusion events
Network representation learning has recently attracted considerable interest, because of its
effectiveness in performing important network analysis tasks such as link prediction and …
effectiveness in performing important network analysis tasks such as link prediction and …
Context-sensitive graph representation learning
Graph representation learning, which maps high-dimensional graphs or sparse graphs into
a low-dimensional vector space, has shown its superiority in numerous learning tasks …
a low-dimensional vector space, has shown its superiority in numerous learning tasks …
Network and Cascade Representation Learning: Algorithms based on Information Diffusion Events
ZT Kefato - 2019 - eprints-phd.biblio.unitn.it
Network representation learning (NRL) and cascade representation learn-ing (CRL) are
fundamental backbones of different kinds of network analysis problems. They are usually …
fundamental backbones of different kinds of network analysis problems. They are usually …