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Re: Surveying the types of argument [via Argumentation Community Group]

From: Tim Clark <tim_clark@harvard.edu>
Date: Wed, 19 Sep 2012 20:38:24 -0400
Cc: Tom Breton <tehom@panix.com>, "public-argumentation@w3.org" <public-argumentation@w3.org>
Message-Id: <673726D1-E7F5-47D6-AF15-E14169237DEC@harvard.edu>
To: Adam Sobieski <adamsobieski@hotmail.com>
As Adam says, there are various forms of "argumentation", and therefore many possible paths for us. I suggest that we think through our goals a bit and focus on some practical use cases to start with.  What practical gains can we hope to target?


Tim Clark
Director of Informatics, MassGeneral Institute for Neurodegenerative Disease
Instructor in Neurology, Harvard Medical School
65 Landsdowne St, 2nd floor
Cambridge MA 02139 USA
mobile: +1 617-947-7098 
skype: 'skypetimc'

On Sep 19, 2012, at 6:32 PM, Adam Sobieski wrote:

> Sounds good, thanks. There are various interpretations possible for "all forms of argumentation"; many can be applicable. One of many possible categorizations of kinds of argumentation includes: conversational, mathematical, scientific, legal, and political [1].
> The list: rationales, disputes, proofs, transcriptions, and short fragments is also useful. In those categories, we can see the applicability of document and multimedia processing; the analysis of audio and video is an interesting topic. There could be other useful categorizations of argumentation as well.
> With regard to multimedia processing, online resources exist, for example CosmoLearning [2], which we could make use of as corpora. On such educational video sites, we might find samples of explanatory rationales, including in sciences, as well as proofs, such as logical and mathematical. Videos of debate can be found online as well.
> A related topic is speech recognition to XML, speech-to-XML, where resultant speech recognition output XML could include mathematical and scientific markup. Transcripts could be XML, XHTML, or HTML5-based.
> Speech recognition technologies on video, including deep neural network approaches [3], can obtain transcripts from the multimedia objects, with accompanying text or hypertext.
> Annotational XML, of use in XML-based transcripts, including XHTML transcripts, could add discourse analytical, argument analytical, as well as other information to XML-based transcripts. Depending upon group interest, a discussion topic could be such annotational formats for multimedia transcripts.
> Kind regards, 
> Adam Sobieski 
> [1] http://en.wikipedia.org/wiki/Argumentation_theory#Kinds_of_argumentation
> [2] http://www.cosmolearning.com/
> [3] http://blogs.technet.com/b/next/archive/2012/06/20/a-breakthrough-in-speech-recognition-with-deep-neural-network-approach.aspx
> [4] http://www.cs.vassar.edu/sigann/

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Received on Thursday, 20 September 2012 00:39:03 UTC

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