Machine-in-the-loop for Knowledge Discovery – Max Kleiman-Weiner ODSC Boston 2015

I’ll present the new knowledge discovery tools we are building at Diffeo. Unlike traditional search engines that use keywords, Diffeo provides an in-browser knowledge base that accelerates information gathering about people, companies, chemical compounds, cyber events, or other real world entities. I’ll describe how Diffeo uses active learning to encourage long and deep user interactions in order to recommend new content for in-progress articles. As you write, the search results get better and more interesting, because the system can see more precisely which entity you mean and which you don’t (disambiguation) and also what you don’t know yet about the entity (discovery).

Finally in this presentation I’ll describe our experience organizing the Text REtrieval Conference (TREC) on Knowledge Base Acceleration (KBA) and Dynamic Domain (DD) which are pushing the state of the art in knowledge discovery on large streams. I’ll show you how to access the largest corpus of streaming text data ever released for public evaluations.

Presenter Bio

Max is a co-founder of Diffeo and computational scientist. Previously Max was a Fulbright Scholar in Beijing and has recently been immersed in the development of Diffeo’s cross language modeling tools. Max has a BS from Stanford where he was a Goldwater Scholar, an MSc from Oxford in Applied Statistics where he was a Marshall Scholar, and he is currently a Hertz and NSF Fellow at MIT.