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<record>
  <title>Cloud-based Recommendation System for E-Commerce</title>
  <journal>Journal of Information &amp; Systems Management</journal>
  <author>GaÅ¡per Slapniar, BoÅ¡tjan Kaluza</author>
  <volume>9</volume>
  <issue>4</issue>
  <year>2019</year>
  <doi>https://doi.org/10.6025/jism/2019/9/4/139-145</doi>
  <url>http://www.dline.info/jism/fulltext/v9n4/jismv9n4_3.pdf</url>
  <abstract>This paper leverages cloud-based machine learning platform to implement an item-based recommendation system for an e-commerce application. The solution is based on Prediction IO platform, which offers a fullstack architecture based on MongoDB database, Hadoop framework for distributed processing, Apache Mahout scalable machine learning library, and RESTful API. We implemented an item-based recommendation engine for product suggestions in an online retail store using realworld data. Preliminary results are quite promising achieving Mean Average Precision of 6 %.</abstract>
</record>
