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Better Informing our Readers through the Dow Jones Knowledge Graph

In today’s world understanding the full context of an event is not an easy thing, especially in a world where there’s countless sources of low quality one dimensional content is fighting for our attention. Which leaves most readers of the news uniformed or spending time piecing together incomplete information. At Dow Jones we are taking advantage of the wealth of data & information we have access to, and modeling out a more complete view of the world so that this additional context can be provided through our knowledge graph. As a result of this effort will be providing those readers that deserve more this missing context through the Wall Street Journal. In this talk we will share what Dow Jones is working towards to better inform our readers through the application of graph technologies, nlp, and a lot of data extraction.
May 6th 2020, 3pm
finance, data extraction, natural language processing, knowledge graph, information extraction, news

Dylan Roy


Dow Jones & Company

Currently works at Dow Jones as the head of engineering for a team that is looking to deliver its customers more relevant information by leveraging big data technologies, graphs, and nlp. Recently relocated from Minneapolis to Barcelona to build the team tasked with working towards this effort. When he isn’t coding he enjoys exploring this new city via bike, and finding new breweries.

Lightening talks from the Main Stage along with speaker Q&A sessions

May 4-7, 2020


Knowledge Graphs form an organized and curated set of facts that provide support for models to help understand the world. This conference gathers technology leaders, researchers, academics, vendors — and most importantly, practitioners, who know the discipline. For KGC 2020, attendees can participate from wherever they want in the world, from the comfort of their homes. We will stream the content, provide access to our speakers and support chat and networking as well as give access to all of the content live and on-demand after the event.