<?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>2026-04-13T07:22:19Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:2117/100880" metadataPrefix="qdc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:2117/100880</identifier><datestamp>2025-07-23T00:25:49Z</datestamp><setSpec>com_2072_1033</setSpec><setSpec>col_2072_452951</setSpec></header><metadata><qdc:qualifieddc xmlns:qdc="http://dspace.org/qualifieddc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://purl.org/dc/elements/1.1/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dc.xsd http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dcterms.xsd http://dspace.org/qualifieddc/ http://www.ukoln.ac.uk/metadata/dcmi/xmlschema/qualifieddc.xsd">
   <dc:title>Market basket analysis in retail</dc:title>
   <dc:creator>Reig Grau, Gerard</dc:creator>
   <dc:subject>Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial</dc:subject>
   <dc:subject>Data mining</dc:subject>
   <dc:subject>Computer algorithms</dc:subject>
   <dc:subject>Market Basket Analysis</dc:subject>
   <dc:subject>Retail</dc:subject>
   <dc:subject>stores</dc:subject>
   <dc:subject>clusters</dc:subject>
   <dc:subject>association rules</dc:subject>
   <dc:subject>data knowledge discovery</dc:subject>
   <dc:subject>Mineria de dades</dc:subject>
   <dc:subject>Algorismes computacionals</dc:subject>
   <dcterms:abstract>En col·laboració amb la Universitat de Barcelona (UB) i la Universitat Rovira i Virgili  (URV)</dcterms:abstract>
   <dcterms:abstract>In this Master Thesis memory will be described a full end-to-end data science project&#xd;
performed in CleverData, a successful start-up specialized in machine learning techniques&#xd;
and analytics tools. Over all its capacities, it offers a huge variety of solutions to nowadays&#xd;
business needs from different domains.&#xd;
This project was performed for one of its client, an important retail company from Spain. It&#xd;
consist of analysing the market basket of customers. Thus, the main goal is to find which&#xd;
items are purchased together in their stores.&#xd;
Through the memory, the reader will see how, step by step, the project grows. Since the first&#xd;
step of defining objectives, until the last one of results delivery. Moreover, the reader will see&#xd;
one of the most promising tools used for machine learning as a service nowadays, BigML.&#xd;
At the end of the project, the reader will have a general idea how data science projects are&#xd;
structured, and how machine learning can be used to solve real problems in today’s&#xd;
companies.</dcterms:abstract>
   <dcterms:issued>2017-01</dcterms:issued>
   <dc:type>Master thesis</dc:type>
   <dc:rights>Open Access</dc:rights>
   <dc:publisher>Universitat Politècnica de Catalunya</dc:publisher>
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