This Is Watson

This is Watson (IBM Journal of Research and Development, Volume 56, Issue: 3.4, 2012)

The entire issue of IBM Journal of Research and Development, Volume 56, Issue: 3.4 as PDF files.

From the table of contents:

This Is Watson

In 2007, IBM Research took on the grand challenge of building a computer system that could compete with champions at the game of Jeopardy!. In 2011, the open-domain question-answering system dubbed Watson beat the two highest ranked players in a nationally televised two-game Jeopardy! match. This special issue provides a deep technical overview of the ideas and accomplishments that positioned our team to take on the Jeopardy! challenge, build Watson, and ultimately triumph. It describes the nature of the question-answering challenge represented by Jeopardy! and details our technical approach. The papers herein describe and provide experimental results for many of the algorithmic techniques developed as part of the Watson system, covering areas including computational linguistics, information retrieval, knowledge representation and reasoning, and machine leaning. The papers offer component-level evaluations as well as their end-to-end contribution to Watson’s overall question-answering performance.

1 Introduction to “This is Watson”
D. A. Ferrucci

2 Question analysis: How Watson reads a clue
A. Lally, J. M. Prager, M. C. McCord, B. K. Boguraev, S. Patwardhan, J. Fan, P. Fodor, and J. Chu-Carroll

3 Deep parsing in Watson
M. C. McCord, J. W. Murdock, and B. K. Boguraev

4 Textual resource acquisition and engineering
J. Chu-Carroll, J. Fan, N. Schlaefer, and W. Zadrozny

5 Automatic knowledge extraction from documents
J. Fan, A. Kalyanpur, D. C. Gondek, and D. A. Ferrucci

6 Finding needles in the haystack: Search and candidate generation
J. Chu-Carroll, J. Fan, B. K. Boguraev, D. Carmel, D. Sheinwald, and C. Welty

7 Typing candidate answers using type coercion
J. W. Murdock, A. Kalyanpur, C. Welty, J. Fan, D. A. Ferrucci, D. C. Gondek, L. Zhang, and H. Kanayama

8 Textual evidence gathering and analysis
J. W. Murdock, J. Fan, A. Lally, H. Shima, and B. K. Boguraev

9 Relation extraction and scoring in DeepQA
C. Wang, A. Kalyanpur, J. Fan, B. K. Boguraev, and D. C. Gondek

10 Structured data and inference in DeepQA
A. Kalyanpur, B. K. Boguraev, S. Patwardhan, J. W. Murdock, A. Lally, C. Welty, J. M. Prager, B. Coppola, A. Fokoue-Nkoutche, L. Zhang, Y. Pan, and Z. M. Qiu

11 Special Questions and techniques
J. M. Prager, E. W. Brown, and J. Chu-Carroll

12 Identifying implicit relationships
J. Chu-Carroll, E. W. Brown, A. Lally, and J. W. Murdock

13 Fact-based question decomposition in DeepQA
A. Kalyanpur, S. Patwardhan, B. K. Boguraev, A. Lally, and J. Chu-Carroll

14 A framework for merging and ranking of answers in DeepQA
D. C. Gondek, A. Lally, A. Kalyanpur, J. W. Murdock, P. A. Duboue, L. Zhang, Y. Pan, Z. M. Qiu, and C. Welty

15 Making Watson fast
E. A. Epstein, M. I. Schor, B. S. Iyer, A. Lally, E. W. Brown, and J. Cwiklik

16 Simulation, learning, and optimization techniques in Watson’s game strategies
G. Tesauro, D. C. Gondek, J. Lenchner, J. Fan, and J. M. Prager

17 In the game: The interface between Watson and Jeopardy!
B. L. Lewis

Whatever your views on AI, Watson is truly impressive computer science.


I first saw this in a tweet by Christopher Phipps.

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