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. Ferrucci2 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-Carroll3 Deep parsing in Watson
M. C. McCord, J. W. Murdock, and B. K. Boguraev4 Textual resource acquisition and engineering
J. Chu-Carroll, J. Fan, N. Schlaefer, and W. Zadrozny5 Automatic knowledge extraction from documents
J. Fan, A. Kalyanpur, D. C. Gondek, and D. A. Ferrucci6 Finding needles in the haystack: Search and candidate generation
J. Chu-Carroll, J. Fan, B. K. Boguraev, D. Carmel, D. Sheinwald, and C. Welty7 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. Kanayama8 Textual evidence gathering and analysis
J. W. Murdock, J. Fan, A. Lally, H. Shima, and B. K. Boguraev9 Relation extraction and scoring in DeepQA
C. Wang, A. Kalyanpur, J. Fan, B. K. Boguraev, and D. C. Gondek10 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. Qiu11 Special Questions and techniques
J. M. Prager, E. W. Brown, and J. Chu-Carroll12 Identifying implicit relationships
J. Chu-Carroll, E. W. Brown, A. Lally, and J. W. Murdock13 Fact-based question decomposition in DeepQA
A. Kalyanpur, S. Patwardhan, B. K. Boguraev, A. Lally, and J. Chu-Carroll14 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. Welty15 Making Watson fast
E. A. Epstein, M. I. Schor, B. S. Iyer, A. Lally, E. W. Brown, and J. Cwiklik16 Simulation, learning, and optimization techniques in Watson’s game strategies
G. Tesauro, D. C. Gondek, J. Lenchner, J. Fan, and J. M. Prager17 In the game: The interface between Watson and Jeopardy!
B. L. Lewis
Whatever your views on AI, Watson is truly impressive computer science.
Enjoy!
I first saw this in a tweet by Christopher Phipps.