Textual graph

Textual graphs (TGs) - are graphs whose nodes correspond to text (sentences or documents), which are widely prevalent.

(С) SimTeG A Frustratingly Simple Approach Improves Textual Graph Learning

Textual Graphs (TGs) offer a graph-based representation of text data where relationships between phrases, sentences, or documents are depicted through edges. TGs are ubiquitous in real-world applications, including citation graphs (Hu et al., 2020; Yang et al., 2016), knowledge graphs (Wang et al., 2021), and social networks (Zeng et al., 2019; Hamilton et al., 2017),

In recent years, TG representation learning follows a two-stage paradigm: (i) upstream: unsupervised feature extraction that encodes text into numeric embeddings, and (ii) downstream: supervised graph representation learning that further transform the embeddings utilizing the graph structure