Ontology learning (ontology extraction, ontology generation, or ontology acquisition) is the automatic or semi-automatic creation of ontologies, including...

In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the...

HCOME-3O) Ontology (information science) Ontology components Ontology double articulation Ontology learning Ontology modularization Semantic decision table...

databases into RDF, identity resolution, knowledge discovery and ontology learning. The general process uses traditional methods from information extraction...

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from...

Mamba is a deep learning architecture focused on sequence modeling. It was developed by researchers from Carnegie Mellon University and Princeton University...

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn...

Supervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value...

Q-learning is a model-free reinforcement learning algorithm to learn the value of an action in a particular state. It does not require a model of the...

with learning connections, was introduced already by Frank Rosenblatt in his book Perceptron. This extreme learning machine was not yet a deep learning network...