<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1405-5546</journal-id>
<journal-title><![CDATA[Computación y Sistemas]]></journal-title>
<abbrev-journal-title><![CDATA[Comp. y Sist.]]></abbrev-journal-title>
<issn>1405-5546</issn>
<publisher>
<publisher-name><![CDATA[Instituto Politécnico Nacional, Centro de Investigación en Computación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-55462024000402057</article-id>
<article-id pub-id-type="doi">10.13053/cys-28-4-5309</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Comparison of Approaches for Querying Formal Ontologies via Natural Language]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Lepetit-Ondo]]></surname>
<given-names><![CDATA[Anicet]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Capus]]></surname>
<given-names><![CDATA[Laurence]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Bousso]]></surname>
<given-names><![CDATA[Mamadou]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Laval University Department of Computer and Software Engineering ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Canada</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Thies University Department of Computer Science ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Senegal</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2024</year>
</pub-date>
<volume>28</volume>
<numero>4</numero>
<fpage>2057</fpage>
<lpage>2068</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-55462024000402057&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-55462024000402057&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-55462024000402057&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: The Semantic Web relies on the use of ontologies to ensure data sharing, reuse, and interoperability, thereby representing knowledge comprehensible to computers.However, querying ontologies, often performed using the SPARQL language, becomes a challenge, especially for non-expert users. Barriers include linguistic challenges due to syntactic complexity, the need to understand the underlying ontology structure, potential errors in query formulation, and difficulty expressing complex queries. To make knowledge access more user-friendly, this article explores ontology querying in natural language. We propose a reflection aimed at guiding future domain designers in the interrogation of ontologies in natural language, orienting them in their choice of approach according to the applications they will develop. The study relies on the application of Natural Language Processing (NLP) techniques, integrating tools such as Owlready2, RDFLIB, Protégé2000, and the Python programming language to achieve its goals. Three distinct approaches were evaluated for this purpose. The first approach, scenario-based, was tested on two separate ontologies: one related to university concepts and the other to estate settlement. This approach demonstrates remarkable adaptability across various ontologies. However, its effectiveness is closely linked to the types of scenarios and the specific jargon of the evaluated domain. The other two approaches, one based on SPARQL query patterns and the other on decision tree structure, were evaluated on a specific ontology, estate settlement. They show robust performance in terms of result accuracy. Nevertheless, their effectiveness depends on model training for named entity detection, node list management, and enrichment of SPARQL query patterns, operating exclusively within this particular ontology.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Ontology]]></kwd>
<kwd lng="en"><![CDATA[SPARQL language]]></kwd>
<kwd lng="en"><![CDATA[natural language processing]]></kwd>
<kwd lng="en"><![CDATA[query patterns]]></kwd>
<kwd lng="en"><![CDATA[decision trees]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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