<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-14T08:23:12Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:2117/446650" metadataPrefix="oai_dc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:2117/446650</identifier><datestamp>2026-01-13T04:21:17Z</datestamp><setSpec>com_2072_1033</setSpec><setSpec>col_2072_452950</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
   <dc:title>From clustering to intelligent decision support system: An application to 3D printing</dc:title>
   <dc:creator>Karna, Ashutosh</dc:creator>
   <dc:creator>Gibert, Karina</dc:creator>
   <dc:contributor>Universitat Politècnica de Catalunya. Doctorat en Intel·ligència Artificial</dc:contributor>
   <dc:contributor>Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa</dc:contributor>
   <dc:contributor>Universitat Politècnica de Catalunya. IDEAI-UPC - Intelligent Data sciEnce and Artificial Intelligence Research Group</dc:contributor>
   <dc:subject>Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic</dc:subject>
   <dc:subject>Clustering</dc:subject>
   <dc:subject>3D printers</dc:subject>
   <dc:subject>Pattern discovery</dc:subject>
   <dc:subject>Bootstrap clustering</dc:subject>
   <dc:subject>Intelligent decision support system</dc:subject>
   <dc:description>This study focuses on developing an intelligent decision support system (IDSS) that helps a human operator make data-driven decisions. To put IDSS in production, it is necessary to develop two additional components: one oriented to recognize the cluster of new data and the other a knowledge-based resulting from the interpretation of clusters and further association of actions to each cluster, constituting a knowledge base with the alerts and recommendations associated to every profile. Bootstrap-CURE technique is used to handle the initial component, whereas a meta-clustering framework is suggested for interpreting the clusters and providing recommendations. A detailed strategy is presented for handling a print job, examining patterns, and executing actions through IDSS, thus improving predictive accuracy and operational efficiency. Two distinct machine learning models were developed, one to detect the operational mode and another to choose the best meta-cluster for the type of printing jobs and detained steps are provided for implementing the recommendations.</dc:description>
   <dc:description>Peer Reviewed</dc:description>
   <dc:description>Postprint (published version)</dc:description>
   <dc:date>2024</dc:date>
   <dc:type>Conference report</dc:type>
   <dc:identifier>Karna, A.; Gibert, K. From clustering to intelligent decision support system: An application to 3D printing. A: International Conference of the Catalan Association for Artificial Intelligence. «Artificial Intelligence Research and Development: proceedings of the 26th International Conference of the Catalan Association for Artificial Intelligence». Amsterdam: IOS Press, 2024, p. 194-203. ISBN 978-1-64368-543-4. DOI 10.3233/FAIA240435 .</dc:identifier>
   <dc:identifier>978-1-64368-543-4</dc:identifier>
   <dc:identifier>https://hdl.handle.net/2117/446650</dc:identifier>
   <dc:identifier>10.3233/FAIA240435</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:relation>https://ebooks.iospress.nl/volumearticle/69412</dc:relation>
   <dc:rights>http://creativecommons.org/licenses/by-nc/4.0/</dc:rights>
   <dc:rights>Open Access</dc:rights>
   <dc:rights>Attribution-NonCommercial 4.0 International</dc:rights>
   <dc:format>10 p.</dc:format>
   <dc:format>application/pdf</dc:format>
   <dc:publisher>IOS Press</dc:publisher>
</oai_dc:dc></metadata></record></GetRecord></OAI-PMH>