Ridho Reinanda is an AI Research Scientist who is currently leading the Knowledge Graph team at Bloomberg. He obtained his Ph.D. in Information Retrieval at the University of Amsterdam, where he focused on leveraging knowledge graphs for information retrieval tasks and applying IR techniques for knowledge graph maintenance. Since joining Bloomberg, he has focused on building the Bloomberg Knowledge Graph and integrating it in various downstream applications. He recently published a survey in the Foundations and Trends in Information Retrieval book series, titled "Knowledge Graphs: an Information Retrieval Perspective" with collaborators at Bloomberg and the University of Amsterdam.
2021 Talk: Financial Knowledge Graph at Bloomberg: Applications and Challenges
The Bloomberg Knowledge Graph is a graph-centric representation of entities and relationships in the financial world which connects cross-domain data from various sources within Bloomberg. Recent developments in machine learning, knowledge graphs, and language technology have enabled intelligent ways to uncover interesting patterns amongst data that reveal previously hidden insights. By leveraging the entity and relationship information in the knowledge graph, interesting potential applications emerge, especially when combined with other information such as market data and news stories. This talk details how Bloomberg uses the knowledge graph and semantic technologies to enable various use cases, e.g., to link data across different domains, enrich news stories, and support financial analytics centered around entities. In addition, we will discuss the challenges we face to support these use cases, including representing and storing historical, point-in-time relationships between entities.