Name: Linked Data in Watson: Using Linked Data as Evidence for NLP
Start: 2010-11-16T18:00:00-05:00
End: 2010-11-16T21:00:00-05:00
Location: Hynes Convention Center

Using The Semantic Web To Answer Questions. This is a Lotico Boston Semantic Web event.

Linked Data in Watson:
Using Linked Data as Evidence for Natural Language Processing
Chris Welty
IBM Research

A team at IBM Research is working to build Watson, a computing system that can understand and answer complex questions with enough precision and speed to compete against the best human quiz show competitors https://www.research.i... (https://www.research.ibm.com/deepqa/). As with the previous AI grand challenge attempted at IBM Research, (playing chess at a grand master level) the principle challenges for machines to achieve expert performance are fundamentally different than for people. For Watson, the challenge is not acquiring enough knowledge to answer questions, but understanding the questions well enough to exploit the knowledge it has. In this talk I will discuss the rather non-obvious role that linked open data has played in developing Watson.

6.00 pm Introduction - Marco Neumann, KONA

6.15 pm ISWC 2010 news, review & updates - Sandro Hawke, W3C

6.35 pm Linked Data in Watson: Using Linked Data as Evidence for Natural Language Processing - Chris Welty, IBM Research

Please be advised that we will meet at the Hynes Convention Center in Boston for this special event which is kindly hosted by the Semantic Web Summit (https://www.lotico.com/semsum2010) conference.

Bio

Chris Welty is a Research Scientist at the IBM T.J. Watson Research Center in New York. His 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. He is best known as a co-developer of the OntoClean methodology with Nicola Guarino, and as the co-chair of the W3C RIF working group.

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Linked Data in Watson: Using Linked Data as Evidence for NLP

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