NODES 2022 Best Of! Day 5

21 Dec, 2022

Watch the top rated sessions from NODES during our re-runs! These are recorded sessions from NODES 2022. More videos from NODES: 1) Temporal Graph Analysis – Fabio Montagna In this session, we’ll share our experience with horizon scanning over a graph of medical research papers. By leveraging the author keywords from scientific publications, it’s possible to build a cooccurrence graph with a temporal component provided by the paper publication date. We’ll show how we can analyze trends and evolution patterns using an unsupervised algorithm that assigns roles to author keyword. Speakers: Fabio Montagna Slides: 2) Demystifying Graph Analytics With Visualization – Corey Lanum If you’re serious about finding insights in connected datasets, graph analytics is essential. These sophisticated algorithms from the world of graph theory often assign numeric scores to nodes to help make sense of the data. But business users shouldn’t need data scientist-level expertise to interpret graph analytics. They simply want to know what’s really going on: Who has the most influence? Who is well-connected? Who belongs to which hidden subgroup? So how do we help users understand graph analytics in an intuitive way so that they can make fast business decisions? Graph visualization is a proven method for displaying analytical data to non-experts. It’s effective because it binds analytically derived metrics to instantly recognizable visual properties like color, size, icons, and link widths. This is how developers create powerful graph visualization applications that reveal insights that remain hidden in traditional graph representations. In this session, Corey Lanum, a data visualization expert and Cambridge Intelligence’s chief product evangelist, demonstrates how to present graph analytics in a way that users can understand easily. Using Neo4j’s graph algorithms, along with complementary front-end analytics techniques from KeyLines and ReGraph graph visualization toolkits, he will focus on a fascinating dataset featuring large charitable donations that will reveal key donors, recipients, communities, and interesting donation patterns through the universal language of visualization. Speakers: Corey Lanum Slides: 3) Take Data to the Next Level With Graph Machine Learning – Joinal Ahmed, Chaitra Rava In this session, Joinal Ahmed from Google and Chaitra Ravada from Twitter will discuss why graph machine learning makes more sense than the traditional ML approach and show you how graph ML powers use cases like recommendation systems, fraud detection, and more. They will also teach you how to build a fraud detection solution powered by Neo4j, as well as how to deploy graph-based machine learning models on the cloud. Speakers: Joinal Ahmed, Chaitra Ravada

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