[FoRK] Q re: ConceptNet (also FluidDB)

Stephen Williams sdw at lig.net
Thu Oct 22 02:21:54 PDT 2009

J. Andrew Rogers wrote:
> On Oct 21, 2009, at 12:24 PM, Stephen Williams wrote:
>> I view a lot of the semantic technology as A) a better way to 
>> organize information for straight business purposes and B) often the 
>> best form of bottom-up feeder information that could feed into 
>> knowledge and probabilistic graph reasoning systems.
> A (the?) big problem is that even if A) is true in theory it is not 
> true in practice.  The organization exposed to the user has little 
> relation to the organization under the hood. That impedance mismatch 
> is usually very expensive. Explicitly structured data typically 
> matches common use cases pretty well, a cheap "80/20 rule" optimization.
There was a commercial database product with a very nice Java-based GUI 
that was essentially an RDF-graph based database.  It was not hard to 
understand or use.  Unfortunately, they took the wrong product path.  I 
had several conversations with the founder.  He just deviate from his 
particular viewpoint and he didn't know anything about RDF / semantic ideas.

Anyway, yes, that is true now, however I don't think it is necessarily 
true.  We just need the equivalent of a spreadsheet application to make 
it accessible.  I'm thinking about it, when I can...
>> I'm glad you now see a mapping / equivalence.  I would really like to 
>> focus on proving what my intuition tells me, but have several more 
>> pressing concerns first.  Someone will eventually map the equivalence 
>> of NN with probabilistic relational graph reasoning (Bayesian / 
>> Markov with imprecise reasoning, etc.) and both will be A) unified or 
>> B) both be stronger as a result.
> A lot of work gets done that makes the assumption that classic NN 
> models are inferior approximations of high-order Bayesian models. It 
> may just be a conjecture that is commonly assumed, though it does 
> appear to be obviously true upon non-rigorous inspection. Anyone can 
> add weights to the edges and vertices of a graph, the real trick is 
> deciding where to not put edges even when you have a nominal reason to.
> I've long wondered if there is a relationship between Braess' Paradox 
> and pruning algorithms for graph-like computational models but am too 
> busy/lazy to spend much time thinking about it.

Seems like a different thing to me...  Although I wouldn't be surprised 
if there is some analog.


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