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      Machine Learning Architectures for Scalable and Reliable Subject Indexing

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      Springer International Publishing

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          Building Watson: An Overview of the DeepQA Project

          IBM Research undertook a challenge to build a computer system that could compete at the human champion level in real time on the American TV Quiz show, Jeopardy! The extent of the challenge includes fielding a real-time automatic contestant on the show, not merely a laboratory exercise. The Jeopardy! Challenge helped us address requirements that led to the design of the DeepQA architecture and the implementation of Watson. After 3 years of intense research and development by a core team of about 20 researches, Watson is performing at human expert-levels in terms of precision, confidence and speed at the Jeopardy! Quiz show. Our results strongly suggest that DeepQA is an effective and extensible architecture that may be used as a foundation for combining, deploying, evaluating and advancing a wide range of algorithmic techniques to rapidly advance the field of QA.
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            A Tutorial on Multilabel Learning

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              Computational Linguistics and Deep Learning

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                Author and book information

                Book Chapter
                2017
                September 02 2017
                : 644-647
                10.1007/978-3-319-67008-9_61
                74cc42d0-0655-4cb4-8630-e6242cacd8c0

                http://www.springer.com/tdm

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