klotz: graph*

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  1. The article discusses the misconception that integrating complex graph databases (DBs), query languages (QLs), and analytics tools are necessary for Graph RAG. It emphasizes the distinction between traditional graph use cases and generative AI applications, and the need for a simpler tech stack.
    2024-10-19 Tags: , , , by klotz
  2. This article provides a step-by-step guide on how to extract meaningful features from graphs using NetworkX for machine learning applications. It uses Zachary's Karate Club Network as an example and covers feature extraction at node, edge, and graph levels.
  3. This article introduces Graph RAG, a method for enhancing Language Model (LLM) applications by incorporating knowledge graphs. It explains the limitations of traditional text embedding-based retrieval and how Graph RAG addresses them by providing a global understanding of the knowledge base through community detection and report generation.
    2024-08-23 Tags: , , , by klotz
  4. This article explores how to implement a retriever over a knowledge graph containing structured information to power RAG (Retrieval-Augmented Generation) applications.
  5. This article details a data-driven exploration of owl species, using Wikipedia data to create a network visualization of owl relationships.
  6. Announcing Spanner Graph, a groundbreaking offering that unites purpose-built graph database capabilities with Spanner, our globally consistent and virtually unlimited-scale database.
    2024-08-02 Tags: , , by klotz
  7. This article explains how to import GEDCOM files containing genealogy/ancestry data into Neo4j using AuraDB Free. It includes step-by-step instructions for pre-processing the data with Python, importing the data into Neo4j, and exploring the data using the Neo4j Browser and Neo4j Bloom. The article also provides code examples for adding new relationships to the data and styling the graph visualization.
  8. This article describes how to use GNU Emacs for quick data visualization in combination with Gnuplot. It provides a command that can be used to visualize the correlation of data without needing any setup or specific files. The article also includes an example of a command for generating a graph using a data range selected with a rectangle command copy-rectangle.

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