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Machine Learning for Text Analytics

IBM Debating Technologies - Deep Blue showed the world that a computer can beat a human world champion in chess. Watson used big data analytics to defeat top human contestants in question and answering. Now, IBM debating technologies are ushering in a new era of intelligent computing. The goal of this project is to develop technologies that can assist humans to debate and reason. When it comes to decisions, opinions or points of view, there are no "right" or "wrong" answers. Successful arguments are based on evidence, constructed with perspective, and delivered persuasively. These abilities have always been considered exclusive to humans - until now.

This multi-year cognitive computing project explores scenarios where there isn't only one answer (for example as a Jeopardy! clue). We have demonstrated the ability to generate pro and con claims for controversial topics and will show other elements over time.

The distinctive debating technologies developed in this project can have great practical use in industries such as government, legal, finance, healthcare, and sales, to name just a few. For example, automatic argument construction could serve to dramatically enhance business processes and decision making – whether by providing assisted reasoning for which treatment will work best on a patient, or by helping salespeople to develop persuasive arguments when working with clients in deal negotiations, or by presenting pro and con arguments in support of or against government policies.

IBM research lab - Haifa along with IBM Research labs in India, Dublin, China and Watson are working on this effort; collaborating with teams from the Watson group. More information about the effort can be found at



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Dan Gutfreund, Manager Machine Learning for Text Analytics, IBM Research - Haifa

: Manager Machine Learning for Text Analytics, IBM Research - Haifa


Ran Levy
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Ruty Rinnot
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Daniel Hershcovich
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Roy Bar-Haim
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Yonatan Bilu
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Lena Dankin
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Doron Veltzer
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Liat Ein-Dor
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Eyal Shnarch
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