Also, LarKC project has recently extended MapReduce to handle RDF and OWL. (01)
http://blog.larkc.eu/?p=1761 (02)
Mills (03)
On Jan 15, 2010, at 9:53 AM, John F. Sowa wrote: (04)
> Len,
>
> LY> I found this presentation which compares several practical
>> approaches using experimental data. It also provides a (predicted)
>> time line for future progress.
>>
>
>http://www.larkc.eu/wp-content/uploads/2008/04/larkc-kickoff-meeting-greaves.pdf
>
> That is an interesting presentation. But it never defines the term
> LarKC or even explains the acronym -- that's because it was presented
> at a meeting where people already knew the term.
>
> For the record, LarKC is supposed to be a Large Knowledge Collider.
> Following is a FAQ sheet:
>
> http://wiki.larkc.eu/LarkcProject/FAQ
>
> I recommend the following 6-page overview:
>
> http://www.larkc.eu/wp-content/uploads/2008/05/larkc-icsc08.pdf
>
> Following is a 22 megabyte ppt "vision" with lots of gee-whiz graphics,
> which I wouldn't recommend unless you have a high-speed line:
>
> http://www.larkc.eu/wp-content/uploads/larkc-in-a-nutshell.ppt
>
> A short summary of my views on the project:
>
> 1. I agree with many of the points that Mark Greaves makes in the
> first presentation above.
>
> 2. I strongly endorse one of the goals of the LarKC project:
> "Enriching the current logic-based Semantic Web reasoning
> methods with methods from information retrieval, machine
> learning, information theory, databases, and probabilistic
> reasoning."
>
> 3. I also endorse their goal of removing "the scalability
> barriers of currently existing reasoning systems."
>
> 3. But I have serious doubts about a prediction by Gartner that
> by 2012, 70% of the web pages will be marked up with RDF.
>
> 4. And I am highly skeptical about projects that bring together
> 14 different groups, each blessed with half a million euros,
> with the expectation that they will magically produce a
> major new breakthrough.
>
> Although I believe that XML tags (including RDF) are valuable for
> many purposes, I believe that we can extract much more semantic
> information from raw, untagged natural language texts.
>
> At VivoMind, we have been doing that. And we have achieved goals
> #2 and #3 above without using tagged texts. We have processed
> gigabytes and terabytes of NL text with an ordinary 8-CPU server.
>
> John
>
>
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