Also, LarKC project has recently extended MapReduce to handle RDF and OWL. (01)
On Jan 15, 2010, at 9:53 AM, John F. Sowa wrote: (04)
> LY> I found this presentation which compares several practical
>> approaches using experimental data. It also provides a (predicted)
>> time line for future progress.
> 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:
> I recommend the following 6-page overview:
> 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:
> 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
> 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.
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