This is a Keynote Lecture delivered at the Big Data Analytics Summer School 2019 by Atanas Kiryakov, the Founder and CEO of Ontotext a Semantic Web pioneer, and leading developer of semantic technology and knowledge graphs.
To make adequate decisions, businesses have to combine their databases (e.g. CRM data on clients) with non-proprietary data (e.g. company databases such as Factset, Capital IQ, and Crunchbase). However, combining diverse data from multiple sources is a complex task. Matching concepts and entities across disparate data sources and recognizing their mentions in texts requires disambiguation of their meaning. This comes easy to people, but computers often fail to do right. One big difference is that an average graduate is aware of a broad set of entities and concepts.
We developed technology to build Big Knowledge Graphs and apply cognitive analytics to them to provide entity awareness – a sort of semantic fingerprints derived from interconnected entity descriptions. Ontotext’s FactForge.net service provides such "awareness" the most popular companies and people, as well as locations and other entities. Based on GraphDB, it demonstrates analytics on a knowledge graph of more than 2 billion statements.
The Company Graph combines several open data sources, mapped to the FIBO ontology, and interlinks their entities to 1 million news articles. The demonstration includes the importance ranking of nodes, based on graph centrality; popularity ranking, based on news mentions of the company and its subsidiaries; retrieval of similar nodes in a knowledge graph and determining distinguishing features of an entity using graph embedding.