Large-scale multi-label text classification (LMTC) aims to associate a
d...
Knowledge of how science is consumed in public domains is essential for ...
The catch-up effect and the Matthew effect offer opposing characterizati...
Preprint is a version of a scientific paper that is publicly distributed...
Multi-label text classification refers to the problem of assigning each ...
Graph neural networks (GNNs) have been demonstrated to be powerful in
mo...
Graph representation learning has emerged as a powerful technique for
re...
The COVID-19 Open Research Dataset (CORD-19) is a growing resource of
sc...
Recent years have witnessed the emerging success of graph neural network...
We study the problem of large-scale network embedding, which aims to lea...
We present the design and methodology for the large scale hybrid paper
r...
Social and information networking activities such as on Facebook, Twitte...
The shift from individual effort to collaborative output has benefited
s...
To enable efficient exploration of Web-scale scientific knowledge, it is...
Since the invention of word2vec, the skip-gram model has significantly
a...
Progress in science has advanced the development of human society across...