The Embedding Framework presented here was first developed in 2010 by Dr. Stephanie Bertels from a Systematic Review conducted for the Network for Business Sustainability (NBS) to …

Output Intuition: Find embedding of nodes to d-dimensions so that “similar” nodes in the graph have embeddings that are close together.

domain embedding space. Our approach allows us to engage in a direct “dialogue” about these vectors, to query the LLM with intricate embedding data, and tease out narratives and insights

•A node’s embedding is determined by its context.

A word’s embedding can efficiently be extracted when we know the word’s index Kamath, Liu, and Whitaker. Deep Learning for NLP and Speech Recognition. 2019.

Our work shows the limits of embedding models under the existing single vector paradigm and calls for future research to develop methods that can resolve this fundamental limitation.

Embedding techniques initially focused on words but the attention soon started to shift to other forms. This tutorial will provide a high-level synthesis of the main embedding techniques in …