Improved Results with Vector Search in Knowledge Graphs


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I hope folks have found their way over to the Data Science KC Meetup, but I wanted to make sure everyone noticed this graph-focused event coming up February 8. https://www.meetup.com/data-science-kc/events/298393673/
Join us at the Keystone CoLAB to connect with Kansas City's data science community. Jennifer Reif, Senior Developer Advocate at Neo4j and host of the graphstuff.fm podcast will share about improved results with vector search in knowledge graphs.
Vector search within knowledge graphs enables users to improve responses from their applications by combining the natural-language strength of an LLM and data accuracy of a graph. In this presentation, we will discuss what vector search is, what it looks like in a graph, how to add vectors to enhance the data, and how to use an LLM with graph vector search to harness relevant and contextual responses to questions.
Refreshments will be provided by Neo4j.

Improved Results with Vector Search in Knowledge Graphs