If you look at the CN csv files, you will observe a column labelled
'weight', which is the weight given to each assertion/edge; it can be
thought of as being equivalent to strength in OC. Most of the weights are
either 1 or .5 . But, weights could have both positive and negative
values<http://www.lrec-conf.org/proceedings/lrec2012/pdf/1072_Paper.pdf>;
the more positive the more confident that the assertions are true. And i
haven't found any paper explaining what the upper and lower limit for those
values are. So, I just arbitrarily choose the stv to be (1, 0.5).

:-)


On Tue, Nov 26, 2013 at 4:19 AM, Cosmo Harrigan <notifications@github.com>wrote:

> In opencog/python/conceptnet/to_scm.py:
>
> > +		return stv
> > +	except KeyError:
> > +		if ("  "+ word.upper()) in  corpus_dict:
> > +			stv.mean = float(corpus_dict[("  "+ word.upper())])/twf
> > +			stv.count = .95 # have no reason for this value
> > +			conceptnet_dict[word] = stv
> > +			return stv
> > +		else:	
> > +			stv.mean = 1/(twf + 1)
> > +			stv.count = .95  # have no reason for this value
> > +			conceptnet_dict[word] = stv
> > +			return stv
> > +		
> > +
> > +def write_file(cn_assertion, context): # assertion is a list
> > +	DEFAULT_TV = TruthValue(1,0.5) # 0.5 confidence is used(for links) because that is the weight given to most of the assertions on ConceptNet
>
> Actually, I'm referring to the confidence value of the Links generated by
> the ConceptNet Relations being set to 0.5. Not the words that become nodes.
> (
> https://github.com/AmeBel/opencog/blob/58037b9fde235618205e625217e5d1d88ce0e50e/opencog/python/conceptnet/to_scm.py#L47
> )
>
> —
> Reply to this email directly or view it on GitHub<https://github.com/opencog/opencog/pull/403/files#r7912415>
> .
>