<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Industry Collaborations | CRiSS-LAB</title><link>https://criss-lab.com/category/industry-collaborations/</link><atom:link href="https://criss-lab.com/category/industry-collaborations/index.xml" rel="self" type="application/rss+xml"/><description>Industry Collaborations</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Tue, 01 Jun 2021 00:00:00 +0000</lastBuildDate><image><url>https://criss-lab.com/media/sharing.png</url><title>Industry Collaborations</title><link>https://criss-lab.com/category/industry-collaborations/</link></image><item><title>Revving up Sales: Quantifying Automobile Relatedness and Predicting Next Purchase through Network Embeddings</title><link>https://criss-lab.com/projects/derco1/</link><pubDate>Tue, 01 Jun 2021 00:00:00 +0000</pubDate><guid>https://criss-lab.com/projects/derco1/</guid><description>&lt;style>
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This research project aims to enhance the decision-making process in the automotive industry. We analyzed the complete circulation permit data from 2016 to 2021 to establish a relational network structure of vehicles and their embedding representation. Then, we developed recommendation systems that were fine-tuned using customer data. Consequently, the project intends to provide valuable insights for decision-making that can cater to the needs of current and future customers.
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&lt;p>Send us an email to get more information about this project.&lt;/p>
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