Re: [DL-Learner discussion] Questions on DL-Learner

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Hi Lorenz,

Thank you very much for your answers.
I'm planning to use DL-Learner to learn concept definitions from an 
ontology of holiday destinations (I don't have the ontology yet). I want 
to make sure it is possible to get definitions with 
inferiority/superiority signs (about numerical datatype properties not 
about cardinality restrictions).
For example, I would like to get something like that:
"Definition of a destination which is hot in Winter:
hasJanuaryTemperature x and
hasFebruaryTemperature y and
hasMarchTemperature z and
x>20 and
y>20 and
z>20".

I tried to modify the "father.owl" file (see attachments) in DL-Learner 
examples. I put a "hasAge" datatype property and I deleted "hasChild". I 
was hoping to see if I could get a definition with a 
superiority/inferiority sign about age. I got that:

DL-Learner 2010-08-07 command line interface
starting component manager ... OK (82ms)
initialising component "OWL file" ... OK (0ms)
initialising component "fast instance checker" ... OK (388ms)
initialising component "pos neg learning problem" ... OK (0ms)
initialising component "OCEL" ... OK (14ms)

starting top down refinement with: Thing (50% accuracy)
more accurate (83,33%) class expression found: male
Exception in thread "main" java.lang.OutOfMemoryError: GC overhead 
limit exceeded
         at java.util.LinkedList.linkLast(Unknown Source)
         at java.util.LinkedList.add(Unknown Source)
         at java.util.LinkedList.clone(Unknown Source)
         at 
org.dllearner.refinementoperators.RhoDRDown.refine(RhoDRDown.java:474)
         at 
org.dllearner.refinementoperators.RhoDRDown.refine(RhoDRDown.java:498)
         at 
org.dllearner.refinementoperators.RhoDRDown.refine(RhoDRDown.java:470)
         at 
org.dllearner.refinementoperators.RhoDRDown.refine(RhoDRDown.java:413)
         at 
org.dllearner.algorithms.refinement2.ROLearner2.extendNodeProper(ROLearner2.java:551)
         at 
org.dllearner.algorithms.refinement2.ROLearner2.extendNodeProper(ROLearner2.java:521)
         at 
org.dllearner.algorithms.refinement2.ROLearner2.start(ROLearner2.java:436)
         at 
org.dllearner.algorithms.refinement2.ROLComponent2.start(ROLComponent2.java:441)
         at org.dllearner.cli.Start.start(Start.java:347)
         at org.dllearner.cli.Start.main(Start.java:209)

Kind regards,
Céline

Le 10.04.2014 00:02, Lorenz Bühmann a écrit :
> Hi Céline,
>
> of course we can give you more information about DL-Learner if you're
> interested in.
>
> 1.) I'm not exactly sure what you mean by target language, but if if 
> you
> refer to what's the expressivity of the learned class expressions, 
> then
> no, the target language of DL-Learner is not ALC.
> Depending on the used learning algorithm, DL-Learner of course 
> supports
> datatype properties and for example can also learn class expressions
> which consist of constructs used in Description Logics beyond ALC, 
> like
> for example qualified cardinality restrictions(Q).
>
> 2.) see 1.)
>
> 3.) We do not have any numbers, but in general the internally used 
> OWL
> reasoner(e.g. Pellet or HermiT) might be a bottleneck. If you're able 
> to
> just load the necessary part of the ontology, this can of course
> positively influence the learning process. Maybe we're both taking 
> about
> different things when using the term "noise", but I wouldn't declare
> unnecessary information as noise.
>
> 4.) Limits in which sense?
>
> Can you give us any insights into what you're planning to do with the
> DL-Learner?
>
>
> Kind regards,
> Lorenz
> On 04/08/2014 09:00 AM, alec wrote:
>> Hello,
>>
>> I am a PhD student in Laboratoire de Recherche en Informatique in
>> Université Paris Sud (France). I have read papers on DL-Learner. For 
>> my
>> thesis project, I might be interested in using an ILP tool to learn
>> concept definitions. But the ontology I will use as input will have
>> datatype properties (numerical values) and I would like to use a 
>> tool
>> which can learn
>> definitions using these datatype properties.
>>
>> I would like to have some additional information on DL-Learner if it 
>> is
>> possible. I would be grateful if you could answer my questions.
>>
>> 1. I understood that the target language of your algorithm is ALC
>> description logic. Can you confirm me that we cannot get a 
>> definition of
>> a concept with datatype properties (other than string datatype
>> properties)?
>> For example, something like an adult is a person whose age hasValue 
>> x
>> with x>=18.
>>
>> 2. If I understood right:
>> Is there a particular reason for that? Has it a real complexity to
>> implement? Or do you know tools (open source or free of charge for
>> academic research) that can generate a definition with numerical
>> datatype properties (e.g. in SHOIN(D) description logic)?
>>
>> 3. Are there any constraints about the input ontology? Can it be a 
>> big
>> ontology with potential information which is not interesting for
>> defining a concept (i.e. with noise)? Or has it to be just the
>> interesting part of the ontology?
>>
>> 4. Can you say what the limits of DL-Learner are?
>>
>> I would greatly appreciate any help you might be able to give me.
>>
>> Best regards,
>> Céline Alec
>>
>> 
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