<?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>S1405-55462022000100149</article-id>
<article-id pub-id-type="doi">10.13053/cys-26-1-4160</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[A Behavior Analysis of the Impact of Semantic Relationships on Topic Discovery]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Lezama Sánchez]]></surname>
<given-names><![CDATA[Ana Laura]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Tovar Vidal]]></surname>
<given-names><![CDATA[Mireya]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Reyes Ortiz]]></surname>
<given-names><![CDATA[José Alejandro]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Benemérita Universidad Autónoma de Puebla Facultad de Ciencias de la Computación ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Autónoma Metropolitana Departamento de Sistemas ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2022</year>
</pub-date>
<volume>26</volume>
<numero>1</numero>
<fpage>149</fpage>
<lpage>160</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-55462022000100149&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-55462022000100149&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-55462022000100149&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Information Technologies have generated large amounts of documents available for analysis and use. Information systems can provide the user with the necessary data for a specific purpose without human intervention, saving time in providing the response expected by the user. Some traditional models of topic discovery provide essential information in the literature, but it is still necessary to incorporate the knowledge that a person can use when reading a document. In this work, an analysis of the behavior of the techniques of Latent Dirichlet Analysis, Latent Semantic Analysis, and Probabilistic Latent Semantic Analysis is carried out incorporating the semantic relationships of the type hypernym, hyponym, synonymy, holonymy, and meronymy extracted from an external source of knowledge as WordNet. In order to improve the results obtained by applying the three mentioned techniques in a set of documents without adding external knowledge. Compared to the initial results, our experimental results improved when incorporating semantic relationships, such as hypernyms and synonyms. The best result was obtained when using the Lesk algorithm for word sense disambiguation and subsequently applying Latent Dirichlet Analysis.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Topic discovery]]></kwd>
<kwd lng="en"><![CDATA[Latent Semantic Analysis (LSA)]]></kwd>
<kwd lng="en"><![CDATA[Probabilistic Latent Semantic Analysis (PLSA)]]></kwd>
<kwd lng="en"><![CDATA[WordNet]]></kwd>
<kwd lng="en"><![CDATA[Latent Dirichlet Analysis (LDA)]]></kwd>
</kwd-group>
</article-meta>
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