IBM Research-Tokyo

IBM researchers receive IPSJ Kiyasu Special Industrial Achievement Award 2012

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At its annual meeting this month, the Information Processing Society of Japan (IPSJ) recognized IBM Research – Tokyo’sKoichi Takeda and Hiroshi Kanayama with the 2012 Kiyasu Special Industrial Achievement Award for their achievements in the research and development of Question Answering (QA) technology. The award, funded by a donation from the family of the late IPSJ honorary member Prof. Zenichi Kiyasu, recognizes outstanding contributions to the industry.
QA technology, most recognizably used in IBM’s Watson computer system, takes a question expressed in natural language (such as the text on this page, for example), and seeks to understand it in much greater detail to return a precise response. Koichi and Hiroshi led the effort behind Watson’s ability to attach meaning to the words, expressed as clues, on the quiz show Jeopardy! in 2011.
The need to understand a wide variety of subjects to play Jeopardy! demanded a new approach to QA computing confidence and speed for Watson to succeed.
“The traditional approach in QA technology needed to set rules in order to answer questions in a particular field. Before Watson, the existing technology was incapable of answering ambiguous questions written in natural languages, or questions outside its programmed areas of expertise. By taking a more-flexible approach to how Watson stored massive amounts of data, quickly extracted and indexed information, and calculated a statistical bias, it was able to understand the broad range of topics on Jeopardy! — and win,” Hiroshi said as he looked back to his time as a member of the Watson project.
“The biggest reason for Watson’s victory on Jeopardy! was that it could store and access a wealth of high quality information put into its system. But perhaps the biggest reason that Watson drew such significant attention was because of its promise as a technology capable of understanding and finding value in unstructured data, which has exponentially increased in recent years,” Koichi said.
“The QA technology that the Watson project team developed brought further sophistication to the methods for information access. Through the combination of its highly advanced QA technology, and improved text mining technology, intellectual enterprise solutions that integrate structured information with unstructured data (for example, obtained from sensors and social media) will advance many fields of industry.”

Today, Hiroshi and Koichi’s research focuses improving QA technology in a Japanese environment, applying Watson’s QA system in healthcare through collaboration with their colleagues at IBM’s Thomas J. Watson Research Center in the US, and furthering what QA technology can understand, and how we can interact with it.

(Left) Koichi Takeda worked on statistical analysis of background text sources on the Watson project. His research interests include text mining, question answering, and unstructured information management. (Right) Hiroshi Kanayama worked on mining evidence from background text sources. His research interests include syntactic parsing, text mining, and sentiment analysis.
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