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

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Hi,

which version if DL-Learner do you use? The latest version online is 
http://sourceforge.net/projects/dl-learner/files/DL-Learner/dllearner-1.0-beta-2.tar.gz/download 
but we plan to upload a new one as there are many new features and 
bugfixes in the current SVN version.
Form the error message, I assume you use a quite old version. Can you 
try the latest version?

According to the modified example:

You have as positive examples:
stefan -> male, 28
markus -> male, 50
martin -> male, 34
and negative examples:
heinz -> male, 17
anna -> female, 10
michelle -> female, 4

So I guess you want to learn something like
"male AND hasAge integer[>=34]" ?

I'll check if this works, but it should be possible.

Regards,
Lorenz
On 04/10/2014 10:53 AM, alec wrote:
> 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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>>
>>
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