<?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>S1405-55462023000200511</article-id>
<article-id pub-id-type="doi">10.13053/cys-27-2-4119</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Chatbot basado en el aprendizaje profundo para recomendar productos relevantes]]></article-title>
<article-title xml:lang="en"><![CDATA[Chatbot based on Deep Learning for Recommending Relevant Products]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pachas-Santos]]></surname>
<given-names><![CDATA[Luis A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Calderón-Vilca]]></surname>
<given-names><![CDATA[Hugo D.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cárdenas-Mariño]]></surname>
<given-names><![CDATA[Flor C.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional Mayor de San Marcos  ]]></institution>
<addr-line><![CDATA[Lima ]]></addr-line>
<country>Peru</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2023</year>
</pub-date>
<volume>27</volume>
<numero>2</numero>
<fpage>511</fpage>
<lpage>523</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-55462023000200511&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-55462023000200511&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-55462023000200511&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: Las plataformas de compras en línea están creciendo a un ritmo sin precedentes en todo el mundo. Estas plataformas se basan principalmente en motores de búsqueda, que todavía se basan principalmente en la base de conocimientos y utilizan palabras clave que coinciden para encontrar productos similares. Sin embargo, los clientes quieren un enfoque más interactivo que sea conveniente y confiable para consultar productos relacionados. En este artículo, proponemos una idea novedosa de buscar productos en un sistema de compra online utilizando un modelo de chatbot que utiliza Deep Learning el cual procesa imágenes y texto para generar respuestas al cliente. Un usuario puede proporcionar una imagen o dar una descripción del producto que busca, y se le presentarán productos similares basados en imágenes. El sistema de recomendación propuesto se basa en la recuperación de imágenes basadas en el contenido brindado. La evaluación del modelo propuesto se divide en dos partes: si se realiza a través de imágenes genera un 80.6% de precisión y si se realiza por texto presenta un 75% de precisión.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Online shopping platforms are growing at an unprecedented rate around the world. These platforms are mostly based on search engines, which are still mostly knowledge base based and use matching keywords to find similar products. However, customers want a more interactive approach that is convenient and reliable for viewing related products. In this article, we propose a novel idea of searching for products in an online shopping system using a chatbot model that uses Deep Learning which processes images and text to generate responses to the customer. A user can provide a picture or give a description of the product they are looking for, and they will be presented with similar products based on the images. The system of proposed recommendations is based on the recovery of images based on the content provided. The evaluation of the proposed model is divided into two parts: if it is done through images it generates 80.6% accuracy and if it is done through text it has 75% accuracy.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Productos relevantes]]></kwd>
<kwd lng="es"><![CDATA[chatbot]]></kwd>
<kwd lng="es"><![CDATA[machine learning]]></kwd>
<kwd lng="es"><![CDATA[redes neuronales]]></kwd>
<kwd lng="es"><![CDATA[chatbot para ventas]]></kwd>
<kwd lng="en"><![CDATA[Relevant products]]></kwd>
<kwd lng="en"><![CDATA[recommendation]]></kwd>
<kwd lng="en"><![CDATA[chatbot]]></kwd>
<kwd lng="en"><![CDATA[machine learning]]></kwd>
<kwd lng="en"><![CDATA[neural networks]]></kwd>
<kwd lng="en"><![CDATA[selling chatbot]]></kwd>
</kwd-group>
</article-meta>
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