|Date:||2022, May 10|
|Time:||10:30 a. m.|
|Title:||Translation of Natural Language Competency Questions into SPARQL-OWL Queries Using Neural Language Models|
Competency questions are a set of questions in natural language about ontologies, that determine the main scope of a specific ontology. A machine translation of questions simplifies the formulations of them in SPARQL-OWL queries. There are many embedding approaches, that are the main input for the machine encoder. The Word embedding approach is one of the most common approaches, that follows an embedding of vocabularies in a vector representation and feed that to the neural language machine. Word embedding approach applies skip-gram algorithm to sample and generate the training data. This presentation explains about word embedding approach and the skip-gram algorithm.