This article explains how to use Large Language Models (LLMs) to perform document chunking, dividing a document into blocks of text that each express a unified concept or 'idea', to create a knowledge base with independent elements.
This article explores the use of word2vec and GloVe algorithms for concept analysis within text corpora. It discusses the history of word2vec, its ability to perform semantic arithmetic, and compares it with the GloVe algorithm.
