TeKo: Text-Rich Graph Neural Networks with External Knowledge. (arXiv:2206.07253v1 [cs.SI])

Web: http://arxiv.org/abs/2206.07253

Graph Neural Networks (GNNs) have gained great popularity in tackling various
analytical tasks on graph-structured data (i.e., networks). Typical GNNs and
their variants follow a message-passing manner that obtains network
representations by the feature propagation process along network topology,
which however ignore the rich textual semantics (e.g., local word-sequence)
that exist in many real-world networks. Existing methods for text-rich networks
integrate textual semantics by mainly utilizing internal information such as
topics or phrases/words, which often suffer from an inability to …

arxiv graph graph neural networks knowledge networks neural neural networks text