Hi Johannes,
On 1/3/19 4:36 PM, Johannes Castner wrote:
Hi Nil,
I thought to adopt the one for the GO.scm as in this example?
https://github.com/opencog/test-datasets/tree/master/go
It seems that code is more recent
https://github.com/opencog/agi-bio/tree/master/knowledge-import
I have not yet seriously worked on it as I need to first be sure that
the patternminer works on my system and I haven't been able to get
something very simple to work as expected yet. I'll be tinkering again \
I should mention that the new pattern miner is already quite stable. If
you can install opencog on your system, it should work.
...Of course I'd love to share the results and what I'm finding with
you; it'd be great if I can in some ways contribute to your awesome
It would also be of interest to the AGI-Bio team.
system! Does my plan sound reasonable? In terms of timing; I really
need to have a working paper using this system ready before April 1st,
so that I can distribute my dissertation to my committee. This means
that I'd love to have the results as soon as possible; preferably before
the end of January if that is possible?
That seems doable. I should start implementing surprisingness next week.
The time it takes depends on how it is implemented, I'm aiming at
something as general as possible but might also start with something
more specialized, I mean I'll do my best so you have something that
works on time.
Meanwhile if you can run the pattern miner on your data just to make
sure it works so far, maybe even verify at hand that it can find
surprising patterns, etc, would be very good.
Nil
Johannes
On Thursday, January 3, 2019 at 9:52:09 AM UTC, Nil wrote:
On 1/3/19 11:37 AM, Johannes Castner wrote:
> Hi Nil,
>
> Does the new pattern miner support surprisingness yet?
Nope :-(
That's the last missing bit really.
> That's what I'm hoping to make use of.
Great.
I might have recommended you to use the old pattern miner in the
meantime but I'm afraid it's gonna be too buggy. And implementing
surprisingness in the new pattern miner is pretty much my next task,
so...
What is your timing? When do you need this?
If I understand correctly you want to mine patterns in
https://raw.githubusercontent.com/EnvironmentOntology/envo/master/envo.obo
<https://raw.githubusercontent.com/EnvironmentOntology/envo/master/envo.obo>
and I suppose you already have some scripts to turn that into atoms.
Could you share that script? we might want to add it to
https://github.com/opencog/external-tools
<https://github.com/opencog/external-tools>
and maybe turn your use-case into a pattern miner example, that
would be
great.
Nil
>
> Johannes
>
> On Thursday, January 3, 2019 at 9:07:25 AM UTC, Nil wrote:
>
> Hi,
>
> you should use the new pattern miner, see
>
>
https://github.com/opencog/opencog/blob/master/opencog/learning/miner/README.md
<https://github.com/opencog/opencog/blob/master/opencog/learning/miner/README.md>
>
<https://github.com/opencog/opencog/blob/master/opencog/learning/miner/README.md
<https://github.com/opencog/opencog/blob/master/opencog/learning/miner/README.md>>
>
>
> BTW, what doc did you follow to get to that command? I'm
asking so I
> can
> redirect the user to the new pattern miner.
>
> Nil
>
> On 1/1/19 3:57 PM, Johannes Castner wrote:
> > Hi Nil,
> >
> > Thank you, that did that trick. Now I run:
> >
> > guile> (pm-run-patternminer)
> >
> > Yet no matter what knowledge base I run this on it never
seems to
> find any interesting patterns. What could be the cause of that?
> >
> > Johannes
> >
> > On Sunday, December 30, 2018 at 9:43:13 PM UTC, Nil wrote:
> >
> > Hi Johannes,
> >
> > I'm not sure what you mean by compilation but it is
> recommended to
> > disable guile compilation as it makes loading large
data set
> > impractical. For that do as follows
> >
> > guile --no-auto-compile -l my-data.scm
> >
> > where my-data.scm is the file containing your
atomspace data.
> >
> > Hope it helps, let me know otherwise.
> >
> > Nil
> >
> > On 12/30/18 3:02 PM, Johannes Castner wrote:
> > > I'm quite interested in using the pattern miner for
the last
> > chapter of
> > > my dissertation and so I'm excited to work with it
and try
> things
> > out.
> > > However, it seems as though the compilation of even
small
> test
> > knowledge
> > > bases takes a lot of memory? For serious data
sets, such
> as the
> > > environmental ontology
> > >
> >
>
(https://raw.githubusercontent.com/EnvironmentOntology/envo/master/envo.obo
<https://raw.githubusercontent.com/EnvironmentOntology/envo/master/envo.obo>
>
<https://raw.githubusercontent.com/EnvironmentOntology/envo/master/envo.obo
<https://raw.githubusercontent.com/EnvironmentOntology/envo/master/envo.obo>>
>
> >
>
<https://raw.githubusercontent.com/EnvironmentOntology/envo/master/envo.obo
<https://raw.githubusercontent.com/EnvironmentOntology/envo/master/envo.obo>
>
<https://raw.githubusercontent.com/EnvironmentOntology/envo/master/envo.obo
<https://raw.githubusercontent.com/EnvironmentOntology/envo/master/envo.obo>>>)
>
> >
> > > it always crashes. Is there a way to compile the
data in
> a more
> > memory
> > > efficient way, or compile it somehow elsewhere and
upload it?
> > >
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