Skip to Main Content

Graph Database and Analytics Office Hours

Free tips and training every month! Subscribe for reminders and more from Office Hours. FAQ

Header container

December 13, 2018

16:00 UTC   Start Times Around the World

Subscribe to be notified of changes to sessions and give us feedback!

Having trouble watching the video on this page? Open the video in your browser.


Use Cases: When Graphs Meet Machine Learning
In this session, we show how graph technologies can be combined with machine learning techniques, and applied to real-world use cases, using medical, network security, and financial data.

00:00 – Welcome, the story so far. Jean briefly recaps previous sessions (graph intro, architecture)
06:20 – Benefits and main idea of using graphs for data analysis – Sungpack
09:00 – Approach 1: Classical method via graph algorithms. Sungpack shares an example of anomaly detection, using a medicare data set that’s publicly available. Anomalies in treatments provided by specific doctors are identified, which may indicate fraud.
23:40 -- Approach 2: Feeding graph data into a machine learning pipeline by generating features from graph algorithms. Sungpack walks through a security application example, where the problem is detecting malware in a network.
31:05 -- Zeppelin notebook based demo – malware detection
35:40 -- Approach 3: Graph embedding techniques (future directions). Sungpack discusses techniques now in the R&D phase, and possible use cases in life sciences and finance.
55:20 – Resources, Analytics and Data Summit (March 2019) event announcement, and wrapup

Slides are available here:

This is the 6th video in a series. Watch the previous sessions here:

Sign up for future AskTOM graph sessions:

Your Experts

    Sungpack Hong

    Sungpack Hong

    Sungpack Hong is a Research Director at Oracle Labs. He joined Oracle at 2012 after getting his PhD from Stanford University. He leads several research projects regarding graph data processing, large scale data analytics, domain-specific language and machine learning.
    Jean Ihm

    Jean Ihm   

    Jean Ihm is a product manager for Oracle's spatial and graph technologies for database, big data, and cloud platforms. She interacts with customers and partners worldwide, works on product release activities, engages with presales, and helps organize user events. She serves as Oracle liaison to the Spatial and Graph SIG user group, and is a member of the BIWA conference committee. She received a bachelor's degree from MIT, and a law degree from the University of California, Berkeley. She is based at Oracle HQ in Redwood Shores, California.