@article{2865,
  author = {Gašper Slapniar, Boštjan Kaluza},
  title = {Cloud-based Recommendation System for E-Commerce},
  journal = {Journal of Information & Systems Management},
  year = {2019},
  volume = {9},
  number = {4},
  doi = {https://doi.org/10.6025/jism/2019/9/4/139-145},
  url = {http://www.dline.info/jism/fulltext/v9n4/jismv9n4_3.pdf},
  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 %.},
}