Watson is a computer system capable of answering rich natural language questions and estimating its confidence in those answers at a level of the best humans at the task. On Feb 14-16, in an historic event, Watson triumphed over the best Jeopardy! players of all time. In this talk I will discuss how Watson works at a high level with examples from the show.
Bio: Chris Welty is a Research Scientist at the IBM T.J. Watson Research Center in New York. Previously, he taught Computer Science at Vassar College, taught at and received his Ph.D. from Rensselaer Polytechnic Institute, and accumulated over 14 years of teaching experience before moving to industrial research. Chris' principal area of research is Knowledge Representation, specifically ontologies and the semantic web, and he spends most of his time applying this technology to Natural Language Question Answering as a member of the DeepQA/Watson team and, in the past, Software Engineering. Dr. Welty is a co-chair of the W3C Rules Interchange Format Working Group (RIF), serves on the steering committee of the Formal Ontology in Information Systems Conferences, is past president of KR.ORG, on the editorial boards of AI Magazine, The Journal of Applied Ontology, and The Journal of Web Semantics, and was an editor in the W3C Web Ontology Working Group. While on sabbatical in 2000, he co-developed the OntoClean methodology with Nicola Guarino. Chris Welty's work on ontologies and ontology methodology has appeared in CACM, and numerous other publications.