Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY
Eui-Hong Han

Eui-Hong Han
Director, Big Data & Personalization, The Washington Post

Eui-Hong (Sam) Han is the director of big data and personalization at the Washington Post. Sam is an experienced practitioner of data mining and machine learning and has an in-depth understanding of analytics technologies. He has successfully applied these technologies to solve real business problems. At the Washington Post, he leads a team building an integrated big data platform to store all aspects of customer profiles and activities from both digital and print circulation, content metadata, and business data. His team is building an infrastructure, tools, and services to provide personalized experience to customers, empower the newsroom with data for better decisions, and provide targeted advertising capability. Previously, he led the Big Data practice at Persistent Systems, started the Machine Learning Group in Sears Holdings’s online business unit, and worked for a data mining startup company. Sam’s expertise includes data mining, machine learning, information retrieval, and high-performance computing. He holds a PhD in computer science from the University of Minnesota.

Sessions

2:05pm2:45pm Wednesday, September 27, 2017
Secondary topics:  Media, Text
Eui-Hong Han (The Washington Post), Ling Jiang (The Washington Post)
Average rating: ****.
(4.50, 2 ratings)
The quality of online comments is critical to the Washington Post. However, the quality management of the comment section currently requires costly manual resources. Eui-Hong Han and Ling Jiang discuss ModBot, a machine learning-based tool developed for automatic comments moderation, and share the challenges they faced in developing and deploying ModBot into production. Read more.