The amount of textual data on the Web is enormous and it is growing at a rapid pace. However, in comparison to structured in-house data, this is a data source that is hardly utilized for knowledge extraction at all. While there is no shortage of unstructured data, the challenge comes in accessing that data and transforming it into something usable and actionable. In this talk, we will describe how Mito.ai use machine learning and open linked data to tame the continuous stream of unstructured web data. The final product is a personal stock trading assistant where data driven insight about companies, products, employees and markets is made available in a chat based interface.
Jon Espen Ingvaldsen is a passionate computer scientist and skilled software engineer. Throughout his career has had one foot in academia and the other in the industry. Ingvaldsen has a Ph.D. degree related to analysis and monitoring of large data streams. After his PhD, he has worked as a consultant and software engineer for several industrial projects and Postdoc research fellow at NTNU.
As CTO and Co-Founder of Mito.ai, he is leading the development of the next generation trading platform where media monitoring and trading is combined in one chat-based and mobile interface.