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Knowledge Graphs to Power Financial Chat Bots

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.

European Space Agency case study

European Space Agency case study

Hume maps a segment of the space and satellite ecosystem for the European Space Agency

‘The ability to customise Hume Actions via Cypher queries provided ESA with flexibility to cover a range of use cases and customers.’

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Hume Contact Tracing Demo (COVID-19)

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.

Unparalleled Graph Database Scalability Delivered by Neo4j 4.0

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.

Graph-Powered Machine Learning Manning Book by Alessandro Negro, Chief Scientist at GraphAware

Graph-Powered Machine Learning - Book

At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally expressed as graphs. Graph-Powered Machine Learning teaches you how to use graph-based algorithms and data organization strategies to develop superior machine learning applications.

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Knowledge Graphs in Action

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.

Graph Hyper-Growth Ahead: 5-Minute Interview with Kyle McNamara

Interview with Kyle McNamara, CEO, Americas at GraphAware, about how GraphAware works alongside Neo4j (conducted at GraphTour DC 2019)

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To Be or Not To Be, Neo4j Full Text Search Tips and Tricks

Christophe Willemsen, CTO at GraphAware, goes over some tips and tricks on Relevant Search with Neo4j’s Lucene based search engine.

To Be or Not To Be, Neo4j Full Text Search Tips and Tricks

Christophe Willemsen, CTO at GraphAware, goes over some tips and tricks on Relevant Search with Neo4j’s Lucene based search engine.

Social media monitoring with ML-powered Knowledge Graph

Ever wondered how ML can be used to build a Knowledge Graph to allow businesses to successfully differentiate and compete today? We will demonstrate how Computer Vision, NLP/U, knowledge enrichment and graph-native algorithms fit together to build powerful insights from various unstructured data sources.