With the aim to monitor, prevent, and predict cyber attacks on various systems and infrastructures, the cyber defence company needed a solution to ingest and connect all available data and discover threat patterns.
Luanne Misquitta shows how to use the results of a UNION Cypher query.
Luanne Misquitta explains how to produce good starting-point recommendations for whisky using Cypher that are of higher quality than those we see at our favourite online stores.
Vlasta Kůs takes us through converting a corpus of research papers through Natural Language Processing, entity (relation) extraction and graph algorithms to highly informative connected insights organized in a knowledge graph.
This presentation by Christophe Willemsen, CTO, GraphAware, guides you through security best practices for Neo4j development.
Christophe Willemsen, CTO, GraphAware, explains how to apply NLP to extract entities and key phrases to build and search knowledge graphs
Mayank Gupta, SVP of Data and Wren Chan, VP of Foundational Architecture and Innovation from LPL Financial present how they use GraphAware Hume and Neo4j to power financial chat bots.
Demonstration of GraphAware Hume, a graph-powered insights engine. Shows how Hume can be applied to processing and analysing structured data to surface insights. The use case for this demo is coronavirus contact tracing and smart quarantine.
This session features Dr. Alessandro Negro, noted graph database author and Chief Scientist at GraphAware, along with Patrick Wall, Director of Product Marketing at Neo4j. During this webinar, GraphAware explores the powerful scalability features of Neo4j 4.0 in a live demo using the COVID-19 Open Research Dataset.
In this five-minute interview (conducted at GraphTour NYC 2019), Neo4j caught up with Michal and spoke with him about everything from Neo4j 4.0 to funky use cases.
In this presentation, you’ll learn how companies are building Knowledge Graphs with Neo4j and the Hume platform in order to surface previously undiscoverable insights. We’ll go over the process of analysing unstructured data using Machine Learning techniques and how graphs are a wonderful representation for storing Knowledge, making it naturally connectable. Lastly, a Graph Visualisation demonstration will take place, showing new insights discovered from the results of the previous operations.