Mike Tung | Automated Knowledge Graphs For Market Intelligence
KGC 2021 Conference, Workshops and Tutorials
•
22m
Nearly every business is constantly trying to identify, analyze, and grow their market. Yet, traditional processes for data management inevitably lead to a database that contains missing, outdated, invalid, or inconsistent data. Automated knowledge graph construction techniques are a scalable way to maintain and enforce the quality of data in real-world business databases and knowledge graphs offer an ideal representation for modeling the complex relationships between business entities and for validating properties and constraints. In this presentation, we will cover lessons learned building a commercial system that maintains 250M business entities and automatically updates over 100M new facts each month as the external world changes.
Up Next in KGC 2021 Conference, Workshops and Tutorials
-
Michael Cafarella | Infrastructure Fo...
Social Knowledge Graphs such as Wikidata have become massive successes, obtaining a level of coverage and quality that would be the envy of many traditional relational database engineering projects. And yet the downstream use scenarios for such datasets remain sharply limited compared to the vast...
-
Melliyal Annamalai | Developing Enter...
Application developers often need to work with a variety of data types, data models, and workloads within an application. Oracle Database is a multi-model, multi-workload data platform with model-specific tools and technologies, enabling developers to build integrated applications while taking a...
-
Maulik Kamdar | Elsevier's Healthcare...
Knowledge Graphs are increasingly being developed and leveraged in academia and industry to tackle complex biomedical challenges, such as drug discovery and safety, medical literature search, clinical decision support, and disease monitoring and management. In this talk, we will present the resea...