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ontolearn 0.8.0

28 Oct 17:02
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We are happy to share with you our newest release v0.8.0.

Please upgrade as usual:

pip install -U ontolearn

This new release features some refactoring done to ontolearn, among others, highlighting the removal of ModelAdapter, code adjustments due to owlapy's newest versions and refactoring done for Enexa project. Other major changes include integration of NCES in ontolearn-web service as well as fixes DL-learner binding and some changes to our triple store related classes. Work to improve the triple store experience is still in progress.

@Louis-Mozart and @sapkotaruz11 have made their first contributions to the project. Your contribution is well appreciated.

You can check the notes below about PRs and specific commits of interest:

What's Changed

New Contributors

Full Changelog: 0.7.3...0.8.0

ontolearn 0.7.3

01 Aug 14:24
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Version 0.7.3 now out!

Install/upgrade:

pip install -U ontolearn

Full Changelog: 0.7.2...0.7.3

What's Changed

Full Changelog: 0.7.2...0.7.3

ontolearn 0.7.2

11 Jul 12:35
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Happy to share with you our new release: ontolearn 0.7.2

pip install -U ontolearn

Important API changes:

Modules inside ontolearn/base directory removed from ontolearn and classes belonging to those modules are now moved to owlapy.

Respective PRs:

Documentation guides for the classes are also moved to owlapy's documentation which you can find here.

What's Changed

New Contributors

Full Changelog: 0.7.1...0.7.2

ontolearn 0.7.1

09 May 06:46
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ontolearn 0.7.1 is now released!

pip install -U ontolearn

Important Updates: ontolearn-webservice

ontolearn-webservice --path_knowledge_base KGs/Mutagenesis/mutagenesis.owl

ontolearn-webservice --endpoint_triple_store http://0.0.0.0:9080/sparql

What's Changed

Full Changelog: 0.7.0...0.7.1

ontolearn 0.7.0

07 Mar 16:18
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ontolearn 0.7.0 is now released!

Release Notes:

Drill is now available in Ontolearn:

You can import it as follows:

from ontolearn.learners import Drill

Examples:

  1. examples/concept_learning_evaluation.py
  2. examples/concept_learning_cv_evaluation.py

Tree-based DL Learner (tDL) is now available in Ontolearn:

You can import it as follows:

from ontolearn.learners import TDL

Examples:

  1. examples/concept_learning_evaluation.py
  2. examples/concept_learning_cv_evaluation.py
  3. examples/concept_learning_with_tdl_and_triplestore_kb.py

CLIP is now available in Ontolearn:

You can import it as follows:

from ontolearn.concept_learner import  CLIP

Examples:

  1. examples/concept_learning_cv_evaluation.py

Changes to KnowledgeBase class:

  • You can make type retrieval methods to return the type of OWLNamedIndividual for individuals which do not explicitly specify that type. You can do that by setting the argument include_implicit_individuals of class KnowledgeBase to True. By default it is False.

  • Ontology and reasoner can be accessed directly:

    • From kb.ontology() → To kb.ontology
    • From kb.reasoner() → To kb.reasoner
  • Added methods for triple retrieval:

    • abox → returns all related Abox axioms of a given individual, list of individuals or None (all Abox axioms).
    • tbox → method returns all related Tbox axioms of a given concept, data property, object property, a list of them or None (all Tbox axioms)
    • triples → returns all triples of the ontology.

    Return type in 3 formats defined by the mode argument which accepts the following strings:
    1) 'native' -> triples are represented as tuples of owlapy objects.
    2) 'iri' -> triples are represented as tuples of IRIs as strings.
    3) 'axiom' -> triples are represented as owlapy axioms.

  • New property methods to retrieve classes/properties:

    • concepts
    • object_properties
    • object_properties
  • Removed triplestore logic (as well as from OWLOntology_Owlready2 and OWLReasoner_Owlready2). It is now moved to ontolearn.triple_store (described below).

Check everything here


Triple Store Knowledge Base:

Added TripleStoreOntology, TripleStoreReasoner and TripleStoreKnowledgeBase.
TripleStoreKnowledgeBase can be initialized using just an SPARQL endpoint and it can be used instead of the KnowledgeBase
to execute a concept learner. All dataset queries are made using SPARQL and are directed to the provided endpoint.

To import:

from ontolearn.triple_store import TripleStoreOntology, TripleStoreReasoner, TripleStoreKnowledgeBase

For more, you can visit the guide in our documentation here , check the API docs and see the examples listed below.

Examples:

  1. examples/concept_learning_via_triplestore_example.py
  2. examples/concept_learning_with_tdl_and_triplestore_kb.py

Documentation and more:

  • At README.md you can find the Benchmark Results which displays the performance of all our learners.

  • Documentation has been updated to the latest changes. You can always access the up-to-date documentation here.

  • Ontosample is now integrated into Ontolearn. We have also added a guide on how to use it as well as an example.

    Note: ontosample is not part of the default dependencies. To get it you should either install it directly or use: pip install ontolearn[full].


Changes on dependencies:

  • We have added some new dependencies and increased the minimum required version for some of them.
  • Some dependencies are made optional. You can now install all of them or just the minimum required ones.
    • pip install ontolearn[min] → the default one when you execute pip install ontolearn
    • pip install ontolearn[full] → to install the extra dependenices.
      You can check them here.

Bug Fixes and others:

  • Fixed a bug where using the same EvoLearner model to fit more than one learning problem would cause quality drop.
  • Added learning problem generator as Python module
  • Other minor changes that in case you are interested, you can check the PRs comments.

As always you can upgrade with pip:

pip install -U ontolearn

Brought to you by Ontolearn Team.

ontolearn 0.6.1

03 Dec 14:10
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ontolearn 0.6.1

We're happy to announce the 0.6.1 release.

You can upgrade with pip as usual:

pip install -U ontolearn

ontolearn 0.5.4

17 Aug 09:46
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ontolearn 0.5.4

We're happy to announce the 0.5.4 release.

You can upgrade with pip as usual:

pip install -U ontolearn

ontolearn 0.5.3

10 Feb 10:07
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ontolearn 0.5.3

We're happy to announce the 0.5.3 release.

You can upgrade with pip as usual:

pip install -U ontolearn

First Release of Ontolearn

17 Oct 06:50
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Features

  • Properly check domain inclusion in the ConceptGenerator
  • Add Top-Level CNF/DNF conversion

Fixes

  • Fix OCEL (still not equivalent of the DL-Learner implementation)
  • Fix a bug in the DLSyntaxParser to correctly parse Thing/Nothing
  • Multiple fits for EvoLearner on datasets with data properties
  • Correctly filter super properties in the OWLReasoner_Owlready2

Maintenance

  • Use closed world behaviour for negations per default (FastInstanceChecker)

Todos for the next release