Ihab Ilyas:Saga: Continuous Construction and Serving of Large Scale Knowledge Graphs

 

Time and Date: 12:00 AM, Friday, 13rd Jan.

Title: Saga: Continuous Construction and Serving of Large Scale Knowledge Graphs

Abstract:

In this talk I present Saga, an end-to-end platform for incremental and continuous construction of large scale knowledge graphs. Saga demonstrates the complexity of building such platform in industrial settings with strong consistency, latency, and coverage requirements. In the talk, I discuss challenges around the following: building source adapters for ingesting heterogenous data sources; building entity linking and fusion pipelines for constructing coherent knowledge graphs that adhere to a common controlled vocabulary; updating the knowledge graphs with real-time streams; and finally, exposing the constructed knowledge via a variety of services. Graph services include: low-latency query answering; graph analytics; ML-biased entity disambiguation and semantic annotation; and other graph-embedding services to power multiple downstream applications. Saga is used in production at large scale to power a variety of user-facing knowledge features.

Bio:

Ihab Ilyas is a professor in the Cheriton School of Computer Science and the NSERC-Thomson Reuters Research Chair on data quality at the University of Waterloo. He is currently on leave leading the Knowledge Platform at Apple. His main research focuses on the areas of data science and and data management, with special interest in data quality and integration, knowledge construction, machine learning for structured data, and information extraction. Ihab is a co-founder of Tamr, a startup focusing on large-scale data integration, and he is also the co-founder of inductiv (acquired by Apple), a Waterloo-based startup on using AI for structured data cleaning. He is a recipient of the Ontario Early Researcher Award, a Cheriton Faculty Fellowship, an NSERC Discovery Accelerator Award, and a Google Faculty Award, and he is an ACM Fellow and an IEEE Fellow.