[FoRK] Q re: ConceptNet (also FluidDB)

Jeff Bone jbone at place.org
Wed Oct 21 07:43:43 PDT 2009

JAR asks:

> Are we talking about ConceptNet/OpenMind specifically or semantic  
> web technologies generally?  And how do you define "interesting"?

ConceptNet specifically.  It's got some interesting attributes and  
applications that most of the "strong" ontological systems don't have  
(at least in my own uses of them.) "Interesting" in this case means  
just that --- useful beyond what e.g. Cyc, various rdf / semweb  
technologies, and so on have been in my experience.  Particularly when  
dealing with large and diverse natural language corpuses, CN2/3 (with  
supplemental data) have proven more useful at various extraction,  
classification, and extrapolation tasks than other methods including  
statistical ones, naive bayes, etc.  (For me.  YMMV.)

The actual CN tools themselves aren't as useful (you're correct, toys  
so far) as the knowledge base per se and its data model --- which can  
be easily embedded into a slightly more robust model that more easily  
and effectively handles meta-information such as provenance, etc. ---  
and does so defeasibly if necessary, important for real-world use.   
IMHO, those are the major conceptual problems w/ the rdf-like  
approaches;  representing defeasible information as-such and handling  
reification and self-referentiality.  Do-able, but not in a satisfying  
or particularly practical way.  Other problems include the mapping  
problem, while CN's natural language fragment / semi-structured  
approach works much better for fast-and-loose reasoning over mostly- 
raw texts -- e.g. stretching to various machine learning goals for  
which strong induction and inference engines aren't really well-suited.

Other interesting bits along tangential lines:  FreeBase and its more- 
structured Wikipedia extract (WEX) have been proving useful, but  
*this* --- aside from some of the intended monolithic web-app  
properties --- is *really* interesting from a data model perspective:


In particular check out the talks and articles:




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