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Graph Theory in NLP Applications by abaid daud is a document available to read on EtoBox.
What is Graph Theory in NLP Applications about?
This document discusses using graph theory in natural language processing (NLP). It introduces the topic and challenges in NLP, such as understanding context and meaning. It then explains how graph theory can help solve these challenges by modeling language as graphs with nodes and edges. The document provides examples of how graph neural networks (GNNs) apply deep learning to graph-structured data to make predictions and uncover insights. It describes how GNNs use message passing and sparse math to learn f
- Author
- abaid daud
- Language
- EN