Intelligent Recommendation Engine for Financial Analysts — Geoffrey Horrell, Thomson Reuters
14 Nov, 2017
Geoffrey Horrell — Director, Product Incubation, Thomson Reuters We have all heard about the explosion of data in the last decade and going forward. Financial Analysts are overwhelmed by the deluge of information and struggle to keep on top. Turning that stream of news and research into a knowledge graph allows much more precise targeting and deeper insight. Being able to connect the vast amount of data together in a streamlined and elegant way is where TR and Neo4j have made the biggest difference. TR plans to demonstrate this end to end process using TR tools and Neo4j database culminating in a demonstration of a real time, personalized portal that integrates disparate TR content streams into Neo4j for display in an application. Neo4j is used as the operational graph data store and to personalize the content displayed to each user based on their profile, preferences, and behavioral history. Thomson Reuters Big Open Linked Data Solution combines cutting edge NLP, the worlds largest financial knowledge graph and a unique data integration environment – Data Fusion. Using Neo4J for graph analysis delivered excellent performance at significant scale.