gat2vec: representation learning for attributed graphs

N Sheikh, Z Kefato, A Montresor - Computing, 2019‏ - Springer
Network representation learning (NRL) enables the application of machine learning tasks
such as classification, prediction and recommendation to networks. Apart from their graph …

Sentiment analysis using lexico-semantic features

M Mohd, S Javeed, Nowsheena… - Journal of …, 2024‏ - journals.sagepub.com
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 …

Semi-supervised heterogeneous information network embedding for node classification using 1d-cnn

N Sheikh, ZT Kefato, A Montresor - 2018 Fifth International …, 2018‏ - ieeexplore.ieee.org
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 …

Graph neighborhood attentive pooling

ZT Kefato, S Girdzijauskas - arxiv preprint arxiv:2001.10394, 2020‏ - arxiv.org
Network representation learning (NRL) is a powerful technique for learning low-dimensional
vector representation of high-dimensional and sparse graphs. Most studies explore the …

REFINE: representation learning from diffusion events

ZT Kefato, N Sheikh, A Montresor - … 2018, Volterra, Italy, September 13-16 …, 2019‏ - Springer
Network representation learning has recently attracted considerable interest, because of its
effectiveness in performing important network analysis tasks such as link prediction and …

Context-sensitive graph representation learning

J Qin, X Zeng, S Wu, Y Zou - … Journal of Machine Learning and Cybernetics, 2023‏ - Springer
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 …

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 …