Text Representation Enrichment Utilizing Graph based Approaches: Stock Market Technical Analysis Case Study

@article{Salamat2022TextRE,
  title={Text Representation Enrichment Utilizing Graph based Approaches: Stock Market Technical Analysis Case Study},
  author={Sara Salamat and Nima Tavassoli and Behnam Sabeti and Reza Fahmi},
  journal={ArXiv},
  year={2022},
  volume={abs/2211.16103}
}
Graph neural networks (GNNs) have been utilized for various natural language processing (NLP) tasks lately. The ability to encode corpus-wide features in graph representation made GNN models popular in various tasks such as document classification. One major shortcoming of such models is that they mainly work on homogeneous graphs, while representing text datasets as graphs requires several node types which leads to a heterogeneous schema. In this paper, we propose a transductive hybrid… 
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