dl-learner-discussion — DL-Learner related discussions

Re: [DL-Learner discussion] little bug 2

[Jens L. <le...@in...>]

Hello,

Am 22.02.2014 21:35, schrieb Giuseppe Cota:
> Hi Everyone,
> I'd like to report a little bug. In 
> org.dllearner.learningproblems.ClassLearningMethod.java the setter and 
> the getter for accuracyMethod are missing.

Thanks for pointing this out. I added the methods. If you are interested
in contributing to DL-Learner yourself, please drop me a mail describing
what you are working on and I can grant you SVN access.

Kind regards,

Jens

-- 
Dr. Jens Lehmann
AKSW Group, Department of Computer Science, University of Leipzig
Homepage: http://www.jens-lehmann.org
GPG Key: http://jens-lehmann.org/jens_lehmann.asc

[DL-Learner discussion] little bug 2

[Giuseppe C. <gi...@gm...>]

Hi Everyone,
I'd like to report a little bug. In 
org.dllearner.learningproblems.ClassLearningMethod.java the setter and 
the getter for accuracyMethod are missing.

Greetings,
Giuseppe Cota

Re: [DL-Learner discussion] little bug advise

[Lorenz B. <spo...@st...>]

Hi Giuseppe,

thanks for the hint.

Regards,
Lorenz Bühmann
On 02/04/2014 06:40 PM, Giuseppe Cota wrote:
> To whom it may concern,
> I would like to advise a little bug on line 120 of
> org.dllearner.algorithms.PCELOE.java, in that line you redifine the
> field bestEvaluatedDescriptions, when you run the algorithm the field
> bestEvaluatedDescriptions of PCELOE have elements, but the homonymous
> field of his superclass (AbstractCELA) is empty. Therefore when you
> invoke the method AbstractCELA#getSolutionString(), it does not print
> anything. I think you should just comment the line 120.
>
> Greetings,
> Giuseppe Cota
>
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Re: [DL-Learner discussion] How to create a new component

[Lorenz B. <spo...@st...>]

Hello Giuseppe,

basically the core components are still KnowledgeSource, 
ReasonerComponent, LearningProblem, LearningAlgorithm. Do you think 
about any other components? For the learning taks itself, these are at 
least the ones needed and how it's done in DL-Learner.

Regards,
Lorenz
On 01/27/2014 05:36 PM, Giuseppe Cota wrote:
> To Whom It May Concern,
> I would like to develop some new components and I have a couple of 
> questions to ask (If I may).
>
>  1. I have read the manual and it says that to create a concrete
>     component I have to implement one of the following interfaces:
>     KnowledgeSource, ReasonerComponent, LearningProblem,
>     LearningAlgorithm, but It says also that the list is incomplete.
>     Which are all the interfaces and/or abstract classes that I can
>     implement for the creation of a new component?
>  2. I have read the old code, contained in the "Build 2010-08-07"
>     directory, and the new one. I saw that the management of
>     configuration options of the components changed. Now, for example
>     my component has an option called 'testOption' of String type, I
>     created the setter and getter methods, but I want to set a set of
>     allowed values. With the old version of DLLearner I could do it
>     with StringConfigOption#setAllowedValues method, but how can I do
>     it now with the new policy?
>
> Greetings,
> Giuseppe
>
>
>
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[DL-Learner discussion] little bug advise

[Giuseppe C. <gi...@gm...>]

To whom it may concern,
I would like to advise a little bug on line 120 of 
org.dllearner.algorithms.PCELOE.java, in that line you redifine the 
field bestEvaluatedDescriptions, when you run the algorithm the field 
bestEvaluatedDescriptions of PCELOE have elements, but the homonymous  
field of his superclass (AbstractCELA) is empty. Therefore when you 
invoke the method AbstractCELA#getSolutionString(), it does not print 
anything. I think you should just comment the line 120.

Greetings,
Giuseppe Cota

[DL-Learner discussion] Fwd: How to create a new component

[Giuseppe C. <gi...@gm...>]

To Whom It May Concern,
I would like to develop some new components and I have a couple of 
questions to ask (If I may).

 1. I have read the manual and it says that to create a concrete
    component I have to implement one of the following interfaces:
    KnowledgeSource, ReasonerComponent, LearningProblem,
    LearningAlgorithm, but It says also that the list is incomplete.
    Which are all the interfaces and/or abstract classes that I can
    implement for the creation of a new component?
 2. I have read the old code, contained in the "Build 2010-08-07"
    directory, and the new one. I saw that the management of
    configuration options of the components changed. Now, for example my
    component has an option called 'testOption' of String type, I
    created the setter and getter methods, but I want to set a set of
    allowed values. With the old version of DLLearner I could do it with
    StringConfigOption#setAllowedValues method, but how can I do it now
    with the new policy?

Greetings,
Giuseppe

[DL-Learner discussion] How to create a new component

[Giuseppe C. <giu...@st...>]

To Whom It May Concern,
I would like to develop some new components and I have a couple of 
questions to ask (If I may).

 1. I have read the manual and it says that to create a concrete
    component I have to implement one of the following interfaces:
    KnowledgeSource, ReasonerComponent, LearningProblem,
    LearningAlgorithm, but It says also that the list is incomplete.
    Which are all the interfaces and/or abstract classes that I can
    implement for the creation of a new component?
 2. I have read the old code, contained in the "Build 2010-08-07"
    directory, and the new one. I saw that the management of
    configuration options of the components changed. Now, for example my
    component has an option called 'testOption' of String type, I
    created the setter and getter methods, but I want to set a set of
    allowed values. With the old version of DLLearner I could do it with
    StringConfigOption#setAllowedValues method, but how can I do it now
    with the new policy?

Greetings,
Giuseppe

Re: [DL-Learner discussion] DL Learner Java 1.7 Bug & Side Effect Question

[Lorenz B. <spo...@st...>]

Hi,

can you provide us the ontology such that we can reproduce the strange 
appearance of rdfs:Resource? Unfortunately, NodeSet as well as Node 
objects use HashSets internally, thus a non-determinsm might occur in 
the OWLAPIReasoner. I guess we'll have to wrap it into TreeSets.

Thanks for the bug report.

Regards,
Lorenz
On 05/03/2013 12:49 AM, Donnie Rivera wrote:
>
> To Whom It May Concern:
>
> My name is Donnie Rivera, and I work at Intelligent Software 
> Solutions. I've taken over Chris Shellenbarger's project over the last 
> year which I've completed several changes to the software. One of the 
> changes included moving from Java 1.6 to Java 1.7 which was the cause 
> for the DL Learner bug to appear. Our software still utilizes DL 
> Learner for what we call the "Hypothesis Refinement" process. During 
> this process DL Learner used to find specific types. Unfortunately 
> with all the changes, DL Learner stopped learning these concepts.
>
> After looking into the problem, I've discovered a bug within DL 
> Learner, but also wanted to get input from the side effect for the 
> current working around.
>
> The issue starts with an assumption made within the OWLAPIReasoner. 
> The getSuperClassesImp() assumes that an ordered 
> NodeSet<OWLClass> will be return from the PelletReasoner. This is true 
> with Java 1.6, but not Java 1.7.  That assumption is what leads to the 
> bug within DL Learner's ClassHierarchy. thinOutSubsumptionHierarchy() 
> process.
>
> During the cloneAndRestrict() restrict process, DL Learner's 
> OWLAPIReasoner. getFirstClasses() grabs the first node from the 
> NodeSet<OWLClass> that was returned from the PelletReasoner. This is 
> the cause of the problem because classes are getting mapped to both 
> owl:Thing and rdfs:Resource in Java 1.7 whereas in Java .1.6 they were 
> only getting mapped to owl:Thing. Then during the 
> thinOutSubsumptionHierarchy() process, the upward mapping gets horked 
> which is why DL Learner stopped learning specific types.
>
> This is easily worked around by setting the 
> improveSubsumptionHierarchy attribute to false, but what are the side 
> effects from doing so?
>
> Regards,
>
> Donnie Rivera
>
> Software Engineer
>
> Intelligent Software Solutions (ISS)
>
> Work:  (719) 457-0228
>
> Moblie: (719) 242-8522
>
> Email: don...@is... <mailto:don...@is...>
>
>
>
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[DL-Learner discussion] DL Learner Java 1.7 Bug & Side Effect Question

[Donnie R. <don...@is...>]

To Whom It May Concern:

My name is Donnie Rivera, and I work at Intelligent Software Solutions. I've taken over Chris Shellenbarger's project over the last year which I've completed several changes to the software. One of the changes included moving from Java 1.6 to Java 1.7 which was the cause for the DL Learner bug to appear. Our software still utilizes DL Learner for what we call the "Hypothesis Refinement" process. During this process DL Learner used to find specific types. Unfortunately with all the changes, DL Learner stopped learning these concepts.

After looking into the problem, I've discovered a bug within DL Learner, but also wanted to get input from the side effect for the current working around.

The issue starts with an assumption made within the OWLAPIReasoner. The getSuperClassesImp() assumes that an ordered NodeSet<OWLClass> will be return from the PelletReasoner. This is true with Java 1.6, but not Java 1.7.  That assumption is what leads to the bug within DL Learner's ClassHierarchy. thinOutSubsumptionHierarchy() process.

During the cloneAndRestrict() restrict process, DL Learner's OWLAPIReasoner. getFirstClasses() grabs the first node from the NodeSet<OWLClass> that was returned from the PelletReasoner. This is the cause of the problem because classes are getting mapped to both owl:Thing and rdfs:Resource in Java 1.7 whereas in Java .1.6 they were only getting mapped to owl:Thing. Then during the thinOutSubsumptionHierarchy() process, the upward mapping gets horked which is why DL Learner stopped learning specific types.

This is easily worked around by setting the improveSubsumptionHierarchy attribute to false, but what are the side effects from doing so?

Regards,

Donnie Rivera
Software Engineer
Intelligent Software Solutions (ISS)
Work:  (719) 457-0228
Moblie: (719) 242-8522
Email: don...@is...<mailto:don...@is...>

Re: [DL-Learner discussion] Question about calculating accuracy in dllearner

[Jens L. <le...@in...>]

Dear June,

Am 09.11.2012 16:36, schrieb June:
> Hi all,
>
> I am a little confused about the calculation of predictive accuracy
> here. It will be quite grateful if someone in this list can kick out my
> troubles~
>
> Suppose we are doing a leave one out validation, and we want to learn
> the description for concept Female.
> The knowledge base has Female(ANNE), and ANNE is the one left out for
> testing.
> The result of DLLearner is (not Male) in this case, which is quite
> ideal. But how to test whether ANNE is correctly classified? Do we need
> to ask the knowledge base whether (not Male(ANNE)) is true? But the
> knowledge base will always return false for these negated concepts.

In most DL-Learner algorithms, the reasoner and the learning problem is 
configurable. You can find a list of components and options here:

http://dl-learner.svn.sourceforge.net/viewvc/dl-learner/trunk/interfaces/doc/configOptions.html 
(also linked from http://dl-learner.org)

Please also have a look at this paper (and later ones by d'Amato, 
Fanizzi and Esposito:

http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-426/swap2008_submission_14.pdf

In essence, there are different heuristics for measuring the accuracy of 
concepts. Some of them take specifically the open world assumption of 
OWL into account (which basically results in ternary classification), 
whereas others are standard binary classification methods (predictive 
accuracy, F-measure). DL-Learner can be configured to use different 
measures - the exact details depend on your specific requirements.

Another directly related issue are the reasoners: You can either use a 
standard OWL reasoner (which by default assumes an open world), but you 
could also use the incomplete "fast instance checker" in DL-Learner, 
which makes a closed world assumption (in a nutshell, it computes basic 
inferences on the background ontologies using a standard OWL reasoner, 
but then applies simplified fast instance check algorithms on top of the 
obtained inferences).

By the way, DL-Learner already has an included mechanism for measuring 
cross validation accuracy:
http://dl-learner.svn.sourceforge.net/viewvc/dl-learner/trunk/examples/cross-validation/
(It can also be extended to support "leave one out".)

It's a somewhat lengthy answer, but I hope it helps.

Kind regards,

Jens

-- 
Dr. Jens Lehmann
Head of AKSW/MOLE group, University of Leipzig
Homepage: http://www.jens-lehmann.org
GPG Key: http://jens-lehmann.org/jens_lehmann.asc

Re: [DL-Learner discussion] Question about calculating accuracy in dllearner

[June <zhu...@gm...>]

Hi all,

I am a little confused about the calculation of predictive accuracy 
here. It will be quite grateful if someone in this list can kick out my 
troubles~

Suppose we are doing a leave one out validation, and we want to learn 
the description for concept Female.
The knowledge base has Female(ANNE), and ANNE is the one left out for 
testing.
The result of DLLearner is (not Male) in this case, which is quite 
ideal. But how to test whether ANNE is correctly classified? Do we need 
to ask the knowledge base whether (not Male(ANNE)) is true? But the 
knowledge base will always return false for these negated concepts.

Thanks a lot!

best regards,

June

On 09/22/2012 07:51 AM, Jens Lehmann wrote:
>
> Hi June,
>
> Am 22.09.2012 05:23, schrieb June:
>> Hi, Jens,
>>
>> I have already posted the question to dl-learner mail list, but I have
>> not received the reply yet.
>>
>> I want to check whether the question was received by the mail list. I
>> also checked my status of membership in the mail list, and the result
>> appears I am indeed a member~~
>
> I did reply to the question. Here is the online archive of the list:
> http://sourceforge.net/mailarchive/forum.php?thread_name=505B29B9.9080106%40informatik.uni-leipzig.de&forum_name=dl-learner-discussion 
>
>
> Maybe, the mail went to your spam folder.
>
> Kind regards,
>
> Jens
>
>

[DL-Learner discussion] XKCD Learning problems

[Sebastian H. <hel...@in...>]

Here are a lot of learning problems for DL-Learner and DBpedia ;)
http://xkcd.com/1122/

I have to admit, that we might need some additional data, such as 
election outcomes and such.



-- 
Dipl. Inf. Sebastian Hellmann
Department of Computer Science, University of Leipzig
Events:
* http://sabre2012.infai.org/mlode (Leipzig, Sept. 23-24-25, 2012)
* http://wole2012.eurecom.fr (*Deadline: July 31st 2012*)
Projects: http://nlp2rdf.org , http://dbpedia.org
Homepage: http://bis.informatik.uni-leipzig.de/SebastianHellmann
Research Group: http://aksw.org

Re: [DL-Learner discussion] two questions with dllearner, wait for help, thanks

[nobody <spo...@st...>]

Hi June,

your prefix declaration in the config file is wrong. You have to set the
prefixes which are used in the ontology, and not a path to the file. For
the positive examples the prefix must be
http://www.Department0.University0.edu/ . For the negative examples this
is much more difficult because it seems that the namespace of the
publications depends on the professor. For example
http://www.Department0.University0.edu/AssociateProfessor1/Publication8.
It seems to me that you added all instances which are not positive as
negative examples? You could also use a learning algorithm which only
needs the positive examples.

DL-Learner provides an option for default negation.

Regards,
Lorenz
> Hi list,
>
> I am trying to use DLLearner now, and the version I am using is 1.0
> beta 2, the latest release on the dllearner webpage. But I encountered
> some exceptions. Could anyone here help me to solve this problem? What
> might be the problems with the conf file? Attached are the conf file I
> am using, the error log, and the ontology.
>
> Another question I'd like to know is that in DLLearner is it the case
> that when an instance can not be known (by reasoning maybe) to be an
> individual of a concept, it is not then.
>
> Many thanks!
>
> Best regards,
>
> June
>
>
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[DL-Learner discussion] two questions with dllearner, wait for help, thanks

[June <zhu...@gm...>]

Hi list,

I am trying to use DLLearner now, and the version I am using is 1.0 beta 
2, the latest release on the dllearner webpage. But I encountered some 
exceptions. Could anyone here help me to solve this problem? What might 
be the problems with the conf file? Attached are the conf file I am 
using, the error log, and the ontology.

Another question I'd like to know is that in DLLearner is it the case 
that when an instance can not be known (by reasoning maybe) to be an 
individual of a concept, it is not then.

Many thanks!

Best regards,

June

Re: [DL-Learner discussion] Question about calculating accuracy in dllearner

[Jens L. <le...@in...>]

Hello June,

Am 20.09.2012 14:44, schrieb June:
> Hi, Jens,
>
> I am a little confused about how the accuracy is measured in your paper
> "concept learning in DLs using refinement operator(machine learning
> journal)".
>
> In the API dllearner-1.0-beta-2, suppose 10 solutions can be found with
> 100% accuracy and f-measure for the definition of each concept, and
> together there are 5 concept. How did you calculate your accuracy
> measure in the experiment?
>
> Did you calculate the correct definitions manually in the total 50
> solutions, and then divide by 50? Or select at most one correct
> definition from the solutions for one concept, and calculate the count
> divide by 5? Or else?

In the experiments in the paper [1], we used cross validation [2]. For 
each fold in the validation, we measured (predictive) accuracy [3], i.e. 
the percentage of correctly classified examples (positives and 
negatives). For this, we always only picked the single best solution 
generated by an algorithm. The DL-Learner commandline interface usually 
displays several solutions, but for the experiments only the first one 
is taken into account. I hope this clarifies the issue.

Kind regards,

Jens

[1] http://jens-lehmann.org/files/2010/concept_learning_mlj.pdf
[2] http://en.wikipedia.org/wiki/Cross-validation_%28statistics%29
[3] 
http://en.wikipedia.org/wiki/Accuracy_and_precision#In_binary_classification

-- 
Dr. Jens Lehmann
Head of AKSW/MOLE group, University of Leipzig
Homepage: http://www.jens-lehmann.org
GPG Key: http://jens-lehmann.org/jens_lehmann.asc

[DL-Learner discussion] Question about calculating accuracy in dllearner

[June <zhu...@gm...>]

Hi, Jens,

I am a little confused about how the accuracy is measured in your paper 
"concept learning in DLs using refinement operator(machine learning 
journal)".

In the API dllearner-1.0-beta-2, suppose 10 solutions can be found with 
100% accuracy and f-measure for the definition of each concept, and 
together there are 5 concept. How did you calculate your accuracy 
measure in the experiment?

Did you calculate the correct definitions manually in the total 50 
solutions, and then divide by 50? Or select at most one correct 
definition from the solutions for one concept, and calculate the count 
divide by 5? Or else?

Sorry for asking such a trivial question~

best regards,

June

Re: [DL-Learner discussion] Adding DL Learner Components (specifically, Refinement Operators)

[Jens L. <le...@in...>]

Hello Matthew,

sorry for the very late reply.

Am 29.06.2012 18:37, schrieb Matthew Byrne:
> Hi All
>
> I'm trying to experiment with modifications to DL-Learner initially by
> experimenting with different Refinement Operators. To get the ball
> rolling, I copied RhoDRDown.java and:
> - changed the name to MpbVersion1 and adjusted the annotation to "mpb"
> (where previously there was "rho")
> - included a reference to my new file in the "componentClassNames" list
> of AnnComponentManager.java
> - then tried to run it by changing rho to mpb in an already-working con
> file.
>
> However it does not work.  Any ideas how I can make it work?

In general what you did is correct. However, not all DL-Learner 
components are actually implemented in a flexible way. You got the 
exception, because the used learning algorithm only accepted the 
RhoDRDown refinement operator instead of using an interface. I just 
spend some time to abstract away from this for the CELOE learning 
algorithm, so your problem should now be solved.

I added some documentation here during implementation:
http://dl-learner.org/wiki/WritingComponents

We appreciate further feedback and also source code contributions.

Sorry again for the delay. Usually, we are faster in replying mails.

Kind regards,

Jens

-- 
Dr. Jens Lehmann
Head of AKSW/MOLE group, University of Leipzig
Homepage: http://www.jens-lehmann.org
GPG Key: http://jens-lehmann.org/jens_lehmann.asc

Re: [DL-Learner discussion] Adding DL Learner Components (specifically, Refinement Operators)

[Matthew B. <mat...@gm...>]

Hi Sebastian!

That's right, we met in Dublin last week.  It would be great if I could
commit, yes, but there is quite a good chance that I may not produce
something that is a worthy improvement upon the work...

Thanks - M.

On Fri, Jun 29, 2012 at 6:55 PM, Sebastian Hellmann <
hel...@in...> wrote:

> ** Hi, you were the Matthew i met last week in Dublin right? sorry that i
> forgot to introduce you. i didnt have your email address and i didnt want
> to bother dave and dominic, seeing how busy they are at the moment.
> welcome to the project however. please tell us if we should add your sf
> account to the project so you can commit.
> all the best, sebastian
> --
> Sent with my mobile phone, please excuse my brevity, Sebastian
>
>
> Matthew Byrne <mat...@gm...> wrote:
>>
>> Hi All
>>
>> I'm trying to experiment with modifications to DL-Learner initially by
>> experimenting with different Refinement Operators. To get the ball rolling,
>> I copied RhoDRDown.java and:
>> - changed the name to MpbVersion1 and adjusted the annotation to "mpb"
>> (where previously there was "rho")
>> - included a reference to my new file in the "componentClassNames" list
>> of AnnComponentManager.java
>> - then tried to run it by changing rho to mpb in an already-working con
>> file.
>>
>> However it does not work.  Any ideas how I can make it work?
>>
>> Thanks in advance,
>>
>> Matthew
>>
>> Below is the error that is thrown:
>>
>> Initializing Component "mpb refinement operator"... OK (11ms)
>>
>> An Error Has Occurred During Processing.
>> Cannot convert value of type
>> [org.dllearner.refinementoperators.MpbVersion1] to required type
>> [org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no
>> matching editors or conversion strategy found
>> Stack Trace:
>> java.lang.RuntimeException:
>> org.springframework.beans.factory.BeanCreationException: Error creating
>> bean with name 'alg': Initialization of bean failed; nested exception is
>> org.springframework.beans.ConversionNotSupportedException: Failed to
>> convert property value of type
>> 'org.dllearner.refinementoperators.MpbVersion1' to required type
>> 'org.dllearner.refinementoperators.RhoDRDown' for property 'operator';
>> nested exception is java.lang.IllegalStateException: Cannot convert value
>> of type [org.dllearner.refinementoperators.MpbVersion1] to required type
>> [org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no
>> matching editors or conversion strategy found
>>  at
>> org.dllearner.configuration.spring.DefaultApplicationContextBuilder.buildApplicationContext(DefaultApplicationContextBuilder.java:62)
>>  at org.dllearner.cli.CLI.main(CLI.java:185)
>> Caused by: org.springframework.beans.factory.BeanCreationException: Error
>> creating bean with name 'alg': Initialization of bean failed; nested
>> exception is org.springframework.beans.ConversionNotSupportedException:
>> Failed to convert property value of type
>> 'org.dllearner.refinementoperators.MpbVersion1' to required type
>> 'org.dllearner.refinementoperators.RhoDRDown' for property 'operator';
>> nested exception is java.lang.IllegalStateException: Cannot convert value
>> of type [org.dllearner.refinementoperators.MpbVersion1] to required type
>> [org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no
>> matching editors or conversion strategy found
>>  at
>> org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:527)
>>  at
>> org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:456)
>>  at
>> org.springframework.beans.factory.support.AbstractBeanFactory$1.getObject(AbstractBeanFactory.java:294)
>>  at
>> org.springframework.beans.factory.support.DefaultSingletonBeanRegistry.getSingleton(DefaultSingletonBeanRegistry.java:225)
>>  at
>> org.springframework.beans.factory.support.AbstractBeanFactory.doGetBean(AbstractBeanFactory.java:291)
>>  at
>> org.springframework.beans.factory.support.AbstractBeanFactory.getBean(AbstractBeanFactory.java:193)
>>  at
>> org.springframework.beans.factory.support.DefaultListableBeanFactory.preInstantiateSingletons(DefaultListableBeanFactory.java:585)
>>  at
>> org.springframework.context.support.AbstractApplicationContext.finishBeanFactoryInitialization(AbstractApplicationContext.java:913)
>>  at
>> org.springframework.context.support.AbstractApplicationContext.refresh(AbstractApplicationContext.java:464)
>>  at
>> org.dllearner.configuration.spring.DefaultApplicationContextBuilder.buildApplicationContext(DefaultApplicationContextBuilder.java:60)
>>  ... 1 more
>> Caused by: org.springframework.beans.ConversionNotSupportedException:
>> Failed to convert property value of type
>> 'org.dllearner.refinementoperators.MpbVersion1' to required type
>> 'org.dllearner.refinementoperators.RhoDRDown' for property 'operator';
>> nested exception is java.lang.IllegalStateException: Cannot convert value
>> of type [org.dllearner.refinementoperators.MpbVersion1] to required type
>> [org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no
>> matching editors or conversion strategy found
>>  at
>> org.springframework.beans.BeanWrapperImpl.convertIfNecessary(BeanWrapperImpl.java:485)
>>  at
>> org.springframework.beans.BeanWrapperImpl.convertForProperty(BeanWrapperImpl.java:516)
>>  at
>> org.springframework.beans.BeanWrapperImpl.convertForProperty(BeanWrapperImpl.java:510)
>>  at
>> org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.convertForProperty(AbstractAutowireCapableBeanFactory.java:1406)
>>  at
>> org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.applyPropertyValues(AbstractAutowireCapableBeanFactory.java:1365)
>>  at
>> org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.populateBean(AbstractAutowireCapableBeanFactory.java:1118)
>>  at
>> org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:517)
>>  ... 10 more
>> Caused by: java.lang.IllegalStateException: Cannot convert value of type
>> [org.dllearner.refinementoperators.MpbVersion1] to required type
>> [org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no
>> matching editors or conversion strategy found
>>  at
>> org.springframework.beans.TypeConverterDelegate.convertIfNecessary(TypeConverterDelegate.java:241)
>>  at
>> org.springframework.beans.BeanWrapperImpl.convertIfNecessary(BeanWrapperImpl.java:470)
>>  ... 16 more
>> Terminating DL-Learner...and writing stacktrace to: log/error.log
>>
>

Re: [DL-Learner discussion] Adding DL Learner Components (specifically, Refinement Operators)

[Sebastian H. <hel...@in...>]

Hi, you were the Matthew i met last week in Dublin right? sorry that i forgot to introduce you. i didnt have your email address and i didnt want to bother dave and dominic, seeing how busy they are at the moment.
welcome to the project however. please tell us if we should add your sf account to the project so you can commit. 
all the best, sebastian
--
Sent with my mobile phone, please excuse my brevity, Sebastian

Matthew Byrne <mat...@gm...> wrote:

Hi All


I'm trying to experiment with modifications to DL-Learner initially by experimenting with different Refinement Operators. To get the ball rolling, I copied RhoDRDown.java and:

- changed the name to MpbVersion1 and adjusted the annotation to "mpb" (where previously there was "rho")

- included a reference to my new file in the "componentClassNames" list of AnnComponentManager.java

- then tried to run it by changing rho to mpb in an already-working con file.


However it does not work.  Any ideas how I can make it work? 


Thanks in advance,


Matthew


Below is the error that is thrown:


Initializing Component "mpb refinement operator"... OK (11ms)

An Error Has Occurred During Processing.

Cannot convert value of type [org.dllearner.refinementoperators.MpbVersion1] to required type [org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no matching editors or conversion strategy found

Stack Trace: 

java.lang.RuntimeException: org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'alg': Initialization of bean failed; nested exception is org.springframework.beans.ConversionNotSupportedException: Failed to convert property value of type 'org.dllearner.refinementoperators.MpbVersion1' to required type 'org.dllearner.refinementoperators.RhoDRDown' for property 'operator'; nested exception is java.lang.IllegalStateException: Cannot convert value of type [org.dllearner.refinementoperators.MpbVersion1] to required type [org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no matching editors or conversion strategy found

	at org.dllearner.configuration.spring.DefaultApplicationContextBuilder.buildApplicationContext(DefaultApplicationContextBuilder.java:62)

	at org.dllearner.cli.CLI.main(CLI.java:185)

Caused by: org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'alg': Initialization of bean failed; nested exception is org.springframework.beans.ConversionNotSupportedException: Failed to convert property value of type 'org.dllearner.refinementoperators.MpbVersion1' to required type 'org.dllearner.refinementoperators.RhoDRDown' for property 'operator'; nested exception is java.lang.IllegalStateException: Cannot convert value of type [org.dllearner.refinementoperators.MpbVersion1] to required type [org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no matching editors or conversion strategy found

	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:527)

	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:456)

	at org.springframework.beans.factory.support.AbstractBeanFactory$1.getObject(AbstractBeanFactory.java:294)

	at org.springframework.beans.factory.support.DefaultSingletonBeanRegistry.getSingleton(DefaultSingletonBeanRegistry.java:225)

	at org.springframework.beans.factory.support.AbstractBeanFactory.doGetBean(AbstractBeanFactory.java:291)

	at org.springframework.beans.factory.support.AbstractBeanFactory.getBean(AbstractBeanFactory.java:193)

	at org.springframework.beans.factory.support.DefaultListableBeanFactory.preInstantiateSingletons(DefaultListableBeanFactory.java:585)

	at org.springframework.context.support.AbstractApplicationContext.finishBeanFactoryInitialization(AbstractApplicationContext.java:913)

	at org.springframework.context.support.AbstractApplicationContext.refresh(AbstractApplicationContext.java:464)

	at org.dllearner.configuration.spring.DefaultApplicationContextBuilder.buildApplicationContext(DefaultApplicationContextBuilder.java:60)

	... 1 more

Caused by: org.springframework.beans.ConversionNotSupportedException: Failed to convert property value of type 'org.dllearner.refinementoperators.MpbVersion1' to required type 'org.dllearner.refinementoperators.RhoDRDown' for property 'operator'; nested exception is java.lang.IllegalStateException: Cannot convert value of type [org.dllearner.refinementoperators.MpbVersion1] to required type [org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no matching editors or conversion strategy found

	at org.springframework.beans.BeanWrapperImpl.convertIfNecessary(BeanWrapperImpl.java:485)

	at org.springframework.beans.BeanWrapperImpl.convertForProperty(BeanWrapperImpl.java:516)

	at org.springframework.beans.BeanWrapperImpl.convertForProperty(BeanWrapperImpl.java:510)

	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.convertForProperty(AbstractAutowireCapableBeanFactory.java:1406)

	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.applyPropertyValues(AbstractAutowireCapableBeanFactory.java:1365)

	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.populateBean(AbstractAutowireCapableBeanFactory.java:1118)

	at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:517)

	... 10 more

Caused by: java.lang.IllegalStateException: Cannot convert value of type [org.dllearner.refinementoperators.MpbVersion1] to required type [org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no matching editors or conversion strategy found

	at org.springframework.beans.TypeConverterDelegate.convertIfNecessary(TypeConverterDelegate.java:241)

	at org.springframework.beans.BeanWrapperImpl.convertIfNecessary(BeanWrapperImpl.java:470)

	... 16 more

Terminating DL-Learner...and writing stacktrace to: log/error.log

[DL-Learner discussion] Adding DL Learner Components (specifically, Refinement Operators)

[Matthew B. <mat...@gm...>]

Hi All

I'm trying to experiment with modifications to DL-Learner initially by
experimenting with different Refinement Operators. To get the ball rolling,
I copied RhoDRDown.java and:
- changed the name to MpbVersion1 and adjusted the annotation to "mpb"
(where previously there was "rho")
- included a reference to my new file in the "componentClassNames" list of
AnnComponentManager.java
- then tried to run it by changing rho to mpb in an already-working con
file.

However it does not work.  Any ideas how I can make it work?

Thanks in advance,

Matthew

Below is the error that is thrown:

Initializing Component "mpb refinement operator"... OK (11ms)

An Error Has Occurred During Processing.
Cannot convert value of type
[org.dllearner.refinementoperators.MpbVersion1] to required type
[org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no
matching editors or conversion strategy found
Stack Trace:
java.lang.RuntimeException:
org.springframework.beans.factory.BeanCreationException: Error creating
bean with name 'alg': Initialization of bean failed; nested exception is
org.springframework.beans.ConversionNotSupportedException: Failed to
convert property value of type
'org.dllearner.refinementoperators.MpbVersion1' to required type
'org.dllearner.refinementoperators.RhoDRDown' for property 'operator';
nested exception is java.lang.IllegalStateException: Cannot convert value
of type [org.dllearner.refinementoperators.MpbVersion1] to required type
[org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no
matching editors or conversion strategy found
at
org.dllearner.configuration.spring.DefaultApplicationContextBuilder.buildApplicationContext(DefaultApplicationContextBuilder.java:62)
at org.dllearner.cli.CLI.main(CLI.java:185)
Caused by: org.springframework.beans.factory.BeanCreationException: Error
creating bean with name 'alg': Initialization of bean failed; nested
exception is org.springframework.beans.ConversionNotSupportedException:
Failed to convert property value of type
'org.dllearner.refinementoperators.MpbVersion1' to required type
'org.dllearner.refinementoperators.RhoDRDown' for property 'operator';
nested exception is java.lang.IllegalStateException: Cannot convert value
of type [org.dllearner.refinementoperators.MpbVersion1] to required type
[org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no
matching editors or conversion strategy found
at
org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:527)
at
org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:456)
at
org.springframework.beans.factory.support.AbstractBeanFactory$1.getObject(AbstractBeanFactory.java:294)
at
org.springframework.beans.factory.support.DefaultSingletonBeanRegistry.getSingleton(DefaultSingletonBeanRegistry.java:225)
at
org.springframework.beans.factory.support.AbstractBeanFactory.doGetBean(AbstractBeanFactory.java:291)
at
org.springframework.beans.factory.support.AbstractBeanFactory.getBean(AbstractBeanFactory.java:193)
at
org.springframework.beans.factory.support.DefaultListableBeanFactory.preInstantiateSingletons(DefaultListableBeanFactory.java:585)
at
org.springframework.context.support.AbstractApplicationContext.finishBeanFactoryInitialization(AbstractApplicationContext.java:913)
at
org.springframework.context.support.AbstractApplicationContext.refresh(AbstractApplicationContext.java:464)
at
org.dllearner.configuration.spring.DefaultApplicationContextBuilder.buildApplicationContext(DefaultApplicationContextBuilder.java:60)
... 1 more
Caused by: org.springframework.beans.ConversionNotSupportedException:
Failed to convert property value of type
'org.dllearner.refinementoperators.MpbVersion1' to required type
'org.dllearner.refinementoperators.RhoDRDown' for property 'operator';
nested exception is java.lang.IllegalStateException: Cannot convert value
of type [org.dllearner.refinementoperators.MpbVersion1] to required type
[org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no
matching editors or conversion strategy found
at
org.springframework.beans.BeanWrapperImpl.convertIfNecessary(BeanWrapperImpl.java:485)
at
org.springframework.beans.BeanWrapperImpl.convertForProperty(BeanWrapperImpl.java:516)
at
org.springframework.beans.BeanWrapperImpl.convertForProperty(BeanWrapperImpl.java:510)
at
org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.convertForProperty(AbstractAutowireCapableBeanFactory.java:1406)
at
org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.applyPropertyValues(AbstractAutowireCapableBeanFactory.java:1365)
at
org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.populateBean(AbstractAutowireCapableBeanFactory.java:1118)
at
org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:517)
... 10 more
Caused by: java.lang.IllegalStateException: Cannot convert value of type
[org.dllearner.refinementoperators.MpbVersion1] to required type
[org.dllearner.refinementoperators.RhoDRDown] for property 'operator': no
matching editors or conversion strategy found
at
org.springframework.beans.TypeConverterDelegate.convertIfNecessary(TypeConverterDelegate.java:241)
at
org.springframework.beans.BeanWrapperImpl.convertIfNecessary(BeanWrapperImpl.java:470)
... 16 more
Terminating DL-Learner...and writing stacktrace to: log/error.log

Re: [DL-Learner discussion] Cannot use Pellet reasoner in DL-Learner

[Lorenz B. <spo...@st...>]

Hi An,

it is difficult to say what going wrong without having your code or at
least a runnable, minimal example and maybe some error stack trace.

Why do you need a default constructor for the PelletReasoner class? As
far as I know, the class works based on the knowledge sources which are
given by the constructor.

Kind regards,

Lorenz
> Hi all,
>
> I tried to use Pellet reasoner with DL-Learner but could not get success.
> The original Pellet reasoner wrapper class lacks of the default 
> constructor (constructor with no parameter).
> I tried to add a default constructor and the reasoner can be initialised 
> and it can load the ontology successfully.
> However, a null pointer exception occurred when the hasTypeImpl() method 
> is called
> (e.g. by the learning problem component for the coverage/accuracy 
> calculation).
>
> Are there anyone can use this reasoner? I would appreciate for your help 
> so much if you can help me
> to make use of this reasoner in Dl-Learner.
>
> I am trying to use this reasoner because the fast instance checker seems 
> to be very slow when I tried to load
> the ontology in the showering-duration example in DL-Learner repository. 
> It took minutes to load this ontology
> while the Pellet reasoner takes only several seconds (usually less than 
> 10s).
>
> Thanks,
> An.
>
> ------------------------------------------------------------------------------
> Live Security Virtual Conference
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> threat landscape has changed and how IT managers can respond. Discussions 
> will include endpoint security, mobile security and the latest in malware 
> threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/
> _______________________________________________
> dl-learner-discussion mailing list
> dl-...@li...
> https://lists.sourceforge.net/lists/listinfo/dl-learner-discussion
>

[DL-Learner discussion] Cannot use Pellet reasoner in DL-Learner

[Tran C. An <tc...@gm...>]

Hi all,

I tried to use Pellet reasoner with DL-Learner but could not get success.
The original Pellet reasoner wrapper class lacks of the default 
constructor (constructor with no parameter).
I tried to add a default constructor and the reasoner can be initialised 
and it can load the ontology successfully.
However, a null pointer exception occurred when the hasTypeImpl() method 
is called
(e.g. by the learning problem component for the coverage/accuracy 
calculation).

Are there anyone can use this reasoner? I would appreciate for your help 
so much if you can help me
to make use of this reasoner in Dl-Learner.

I am trying to use this reasoner because the fast instance checker seems 
to be very slow when I tried to load
the ontology in the showering-duration example in DL-Learner repository. 
It took minutes to load this ontology
while the Pellet reasoner takes only several seconds (usually less than 
10s).

Thanks,
An.

Re: [DL-Learner discussion] Protege Plugin

[Lorenz B. <spo...@st...>]

Hello,

sorry for the long delay.

Can you please try this version: Protege plugin 0.7beta 
<http://sourceforge.net/projects/dl-learner/files/Protege%20DL-Learner%20Plugin/0.7/Protege-DL-Learner-plugin-0.7-beta.jar/download> 
- it is currently in Beta status, but should work with Protege 4.2beta.

Regards,
Lorenz

On 18.04.2012 20:15, soroosh samadian wrote:
> Hi All,
>
> I'm new to DL-Learner. As part of my experiment I need to integrate 
> some components from DL-Learner into Protege.
>
> As easy as it may seem I am having difficulty installing the plugin. I 
> am using Protege_4.2_alpha on windows 7. I downloaded the link but 
> unzipping the folder will not yield any DL-learner*.jar to be put in 
> Protege's plugin folder. Also when I tried to do it directly from 
> Protege-> Preference... DL-learner plugin does not show on the list of 
> available plugins.
>
> I also downloaded the previous version jar 
> (DL-Learner-protege-plugin.jar) and placed it in the plugin folders. 
> But after editing the (EquivalentTo) nothing related to DL-learner 
> shows up (tried it with both Protege4.2. alpha and beta)
>
>  Help is much appreciated.
>
> Thank you,
>
> Soroush
>
>
> ------------------------------------------------------------------------------
> Better than sec? Nothing is better than sec when it comes to
> monitoring Big Data applications. Try Boundary one-second
> resolution app monitoring today. Free.
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>
>
> _______________________________________________
> dl-learner-discussion mailing list
> dl-...@li...
> https://lists.sourceforge.net/lists/listinfo/dl-learner-discussion

Re: [DL-Learner discussion] Jamon logging

[Sebastian H. <hel...@in...>]

Hm, yes, there are actually two use cases:
1. Finding bottlenecks and improve performance, for this we can really 
use the tools you are suggesting. I used VisualVM sometimes, but I 
always forget that it exists and code without it ^^   So, I guess this 
is tackled, well.  I might apply for yourkit as well.
2. Whenever we are measuring times, however, to put them in a paper we 
will probably need something else than a profiler. On the other hand 
this part is highly client specific and the script that runs the 
experiment should probably do the measurements.  Then everybody can use 
the prefered library.

Thanks, Chris, for clarifying this. I will try and remove all the time 
logging from the core code and put it in interfaces and use Yourkit 
instead.
VisualVM also does not need an eclipse plugin. I think it is a 
standalone app also.

All the best,
Sebastian



On 04/19/2012 10:19 PM, Chris Shellenbarger wrote:
> Hi Sebastian,
>
> It sounds like what you're trying to accomplish is to determine bottlenecks in the DL-Learner software in order to increase performance/reduce memory footprint.  I think this is a really great idea that all projects should do but very few actually think about.
>
> Spring is the object factory responsible for the instantiation of the high level components (KS, LearningProblem, LearningAlgorithm, Reasoners,etc) and their configured dependencies.  So, we could hook into the object instantiation code and pass any instantiated object to the Jamon MonitorFactory.  The downside of this is that it will only monitor the methods defined on an interface as it's using Java dynamic proxies.  So, we'd be able to see performance characteristics at the interface method level.  Basically, we'd see that LearningAlgorithm.start() would take a lot of time, but not the individual components.
>
> If we want to identify bottlenecks in DL-Learner, why don't we use a profiling tool to profile the application?  This would give us performance metrics for every method called during program execution regardless of whether it was behind an interface or not.   Also, there would be no modifications to code to achieve this - we just run the app with the profiler attached.  VisualVM provides this functionality and plugs in with Eclipse (http://bit.ly/JoAv2X).  Personally, I use YourKit (http://yourkit.com/) which is available for free to open source application developers by following the instructions at (http://bit.ly/JoBsse).  It is an incredible tool which I use for all of my programs that I write.
>
> I don't prefer one metrics library over another - I just want to separate the metrics concern away from the algorithms themselves.  This keeps the code lean and easy to understand/maintain.  We've done a lot in the last year towards to further this goal by removing the configuration from the algorithms.
>
> Please let me know what you think about these points and if I'm misunderstanding something.
>
> Thanks,
> Chris
>
>
> -----Original Message-----
> From: Sebastian Hellmann [mailto:hel...@in...]
> Sent: Thursday, April 19, 2012 9:37 AM
> To: Chris Shellenbarger
> Cc: dl-...@li...
> Subject: Re: [DL-Learner discussion] Jamon logging
>
> The general problem I have with AOP is that it adds quite a technology stack on top of DL-Learner. Normally, you will need to install additional eclipse plugins and whatnot to weave the aspect into the program and I would not do this for logging alone.
>
> Jamon is fairly easy to use, but needs some extra cross concern code. On their site however, they state that:
> http://jamonapi.sourceforge.net/#jamonmisc
> "In fact when totally disabled there is NO PERFORMANCE IMPACT whatsoever, as the actual object is returned and not a monitored object."
>
> I really don't care, where we insert the time profiling code, but we should decide on one framework to use and then use it consistently.
>
> I am not so much concerned about third parties in general. DL-Learner's impact would benefit greatly from better speed performance compared to the disadvantage of some cross_cutting Jamon code here and there. I would always opt for the ease of faster finding bottlenecks.
>
> Have you ever used the Metrics system? The page looks nice, but so does the page of http://projectlombok.org/ (with many disadvantages in the end).  Compatibility with VisualVM is also a plus, but I can not judge, whether it is unnecessary overhead.
>
> All th best,
> Sebastian
>
>
>
> On 04/19/2012 04:53 PM, Chris Shellenbarger wrote:
>> Hi Sebastian,
>>      I think leveraging metrics is a good idea, and along with other cross cutting concerns<http://bit.ly/JnbghC>, I think we need to be careful and not let it into the components-core main library.  A better place for it is up at the interfaces(CLI, etc) level as these are the clients which leverage the core library and do all of the instantiation of the objects they require.  The same goes for third parties who are leveraging just the core jar - the responsibility is on the client to inject these types of concerns at runtime.  This is important for various reasons, but an important reason that affects third parties is that some may want to use another metrics library like Metrics<http://metrics.codahale.com/>   rather than Jamon.  Some may want no metrics at all - this is a client specific choice and shouldn't be at the library level.
>>
>> A nice way of implementing cross cutting concerns like these is to use dynamic proxies/aspect oriented programming (AOP).  We can inject these in behind any interface without changing any code.  For the clients produced by the DL-Learner team, this can be injected as an aspect to wrap all interfaces instantiated by the Spring ApplicationContext with monitoring code.
>>
>> Jamon looks like it's using dynamic proxies to wrapper implementations of interfaces - this typically means it can only monitor methods which are on interfaces.  The same holds true for Spring's dynamic proxies - you can't inject proxies with abstract or concrete classes other than through some byte code manipulation (compile time weaving).   A lot of DL-Learner's methods are defined at the Abstract class level - we can probably analyze these and move the appropriate methods up to an interface.  There will be other benefits to components interacting only with interfaces as well.
>>
>> So, to summarize, in our clients (CLI, etc) we can inject an aspect to leverage Jamon monitoring, but we can't monitor methods which aren't defined in an interface.  I believe the client is the place for this type of code to go as it is responsible for instantiating objects- DL-Learner uses Spring for that, but that's not a requirement for third parties.
>>
>> Please let me know your thoughts on this.
>>
>> Thanks,
>> Chris
>>
>> From: Sebastian Hellmann [mailto:hel...@in...]
>> Sent: Wednesday, April 18, 2012 11:55 PM
>> To: dl-...@li...
>> Subject: [DL-Learner discussion] Jamon logging
>>
>> Hi all,
>> maybe we can add these three lines, at a place where all the objects such as Knowledgesources are created?
>> http://jamonapi.sourceforge.net/#monitoringinterfaces
>>
>> import com.jamonapi.proxy.*;
>>
>>
>>
>> // The MyObject() class has to implement MyInterface for monitoring to work.
>>
>> MyInterface myObject = (MyInterface) MonProxyFactory.monitor(new
>> MyObject());
>>
>> myObject.myMethod();// method call will be monitored with JAMon.
>>
>>
>> All the best,
>> Sebastian
>>
>>
>>
>> --
>>
>> Dipl. Inf. Sebastian Hellmann
>>
>> Department of Computer Science, University of Leipzig
>>
>> Projects: http://nlp2rdf.org , http://dbpedia.org
>>
>> Homepage: http://bis.informatik.uni-leipzig.de/SebastianHellmann
>>
>> Research Group: http://aksw.org
>>
>
> --
> Dipl. Inf. Sebastian Hellmann
> Department of Computer Science, University of Leipzig
> Projects: http://nlp2rdf.org , http://dbpedia.org
> Homepage: http://bis.informatik.uni-leipzig.de/SebastianHellmann
> Research Group: http://aksw.org
>
>
>
>


-- 
Dipl. Inf. Sebastian Hellmann
Department of Computer Science, University of Leipzig
Projects: http://nlp2rdf.org , http://dbpedia.org
Homepage: http://bis.informatik.uni-leipzig.de/SebastianHellmann
Research Group: http://aksw.org

Re: [DL-Learner discussion] Jamon logging

[Chris S. <chr...@is...>]

Hi Sebastian,

It sounds like what you're trying to accomplish is to determine bottlenecks in the DL-Learner software in order to increase performance/reduce memory footprint.  I think this is a really great idea that all projects should do but very few actually think about.

Spring is the object factory responsible for the instantiation of the high level components (KS, LearningProblem, LearningAlgorithm, Reasoners,etc) and their configured dependencies.  So, we could hook into the object instantiation code and pass any instantiated object to the Jamon MonitorFactory.  The downside of this is that it will only monitor the methods defined on an interface as it's using Java dynamic proxies.  So, we'd be able to see performance characteristics at the interface method level.  Basically, we'd see that LearningAlgorithm.start() would take a lot of time, but not the individual components.  

If we want to identify bottlenecks in DL-Learner, why don't we use a profiling tool to profile the application?  This would give us performance metrics for every method called during program execution regardless of whether it was behind an interface or not.   Also, there would be no modifications to code to achieve this - we just run the app with the profiler attached.  VisualVM provides this functionality and plugs in with Eclipse (http://bit.ly/JoAv2X).  Personally, I use YourKit (http://yourkit.com/) which is available for free to open source application developers by following the instructions at (http://bit.ly/JoBsse).  It is an incredible tool which I use for all of my programs that I write.

I don't prefer one metrics library over another - I just want to separate the metrics concern away from the algorithms themselves.  This keeps the code lean and easy to understand/maintain.  We've done a lot in the last year towards to further this goal by removing the configuration from the algorithms.

Please let me know what you think about these points and if I'm misunderstanding something.

Thanks,
Chris


-----Original Message-----
From: Sebastian Hellmann [mailto:hel...@in...] 
Sent: Thursday, April 19, 2012 9:37 AM
To: Chris Shellenbarger
Cc: dl-...@li...
Subject: Re: [DL-Learner discussion] Jamon logging

The general problem I have with AOP is that it adds quite a technology stack on top of DL-Learner. Normally, you will need to install additional eclipse plugins and whatnot to weave the aspect into the program and I would not do this for logging alone.

Jamon is fairly easy to use, but needs some extra cross concern code. On their site however, they state that:
http://jamonapi.sourceforge.net/#jamonmisc
"In fact when totally disabled there is NO PERFORMANCE IMPACT whatsoever, as the actual object is returned and not a monitored object. "

I really don't care, where we insert the time profiling code, but we should decide on one framework to use and then use it consistently.

I am not so much concerned about third parties in general. DL-Learner's impact would benefit greatly from better speed performance compared to the disadvantage of some cross_cutting Jamon code here and there. I would always opt for the ease of faster finding bottlenecks.

Have you ever used the Metrics system? The page looks nice, but so does the page of http://projectlombok.org/ (with many disadvantages in the end).  Compatibility with VisualVM is also a plus, but I can not judge, whether it is unnecessary overhead.

All th best,
Sebastian



On 04/19/2012 04:53 PM, Chris Shellenbarger wrote:
> Hi Sebastian,
>     I think leveraging metrics is a good idea, and along with other cross cutting concerns<http://bit.ly/JnbghC>, I think we need to be careful and not let it into the components-core main library.  A better place for it is up at the interfaces(CLI, etc) level as these are the clients which leverage the core library and do all of the instantiation of the objects they require.  The same goes for third parties who are leveraging just the core jar - the responsibility is on the client to inject these types of concerns at runtime.  This is important for various reasons, but an important reason that affects third parties is that some may want to use another metrics library like Metrics<http://metrics.codahale.com/>  rather than Jamon.  Some may want no metrics at all - this is a client specific choice and shouldn't be at the library level.
>
> A nice way of implementing cross cutting concerns like these is to use dynamic proxies/aspect oriented programming (AOP).  We can inject these in behind any interface without changing any code.  For the clients produced by the DL-Learner team, this can be injected as an aspect to wrap all interfaces instantiated by the Spring ApplicationContext with monitoring code.
>
> Jamon looks like it's using dynamic proxies to wrapper implementations of interfaces - this typically means it can only monitor methods which are on interfaces.  The same holds true for Spring's dynamic proxies - you can't inject proxies with abstract or concrete classes other than through some byte code manipulation (compile time weaving).   A lot of DL-Learner's methods are defined at the Abstract class level - we can probably analyze these and move the appropriate methods up to an interface.  There will be other benefits to components interacting only with interfaces as well.
>
> So, to summarize, in our clients (CLI, etc) we can inject an aspect to leverage Jamon monitoring, but we can't monitor methods which aren't defined in an interface.  I believe the client is the place for this type of code to go as it is responsible for instantiating objects- DL-Learner uses Spring for that, but that's not a requirement for third parties.
>
> Please let me know your thoughts on this.
>
> Thanks,
> Chris
>
> From: Sebastian Hellmann [mailto:hel...@in...]
> Sent: Wednesday, April 18, 2012 11:55 PM
> To: dl-...@li...
> Subject: [DL-Learner discussion] Jamon logging
>
> Hi all,
> maybe we can add these three lines, at a place where all the objects such as Knowledgesources are created?
> http://jamonapi.sourceforge.net/#monitoringinterfaces
>
> import com.jamonapi.proxy.*;
>
>
>
> // The MyObject() class has to implement MyInterface for monitoring to work.
>
> MyInterface myObject = (MyInterface) MonProxyFactory.monitor(new 
> MyObject());
>
> myObject.myMethod();// method call will be monitored with JAMon.
>
>
> All the best,
> Sebastian
>
>
>
> --
>
> Dipl. Inf. Sebastian Hellmann
>
> Department of Computer Science, University of Leipzig
>
> Projects: http://nlp2rdf.org , http://dbpedia.org
>
> Homepage: http://bis.informatik.uni-leipzig.de/SebastianHellmann
>
> Research Group: http://aksw.org
>


--
Dipl. Inf. Sebastian Hellmann
Department of Computer Science, University of Leipzig
Projects: http://nlp2rdf.org , http://dbpedia.org
Homepage: http://bis.informatik.uni-leipzig.de/SebastianHellmann
Research Group: http://aksw.org