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Journal of Information & Systems Management (JISM)

Cloud-based Recommendation System for E-Commerce

GaÃ…Â¡per Slapniar, BoÃ…Â¡tjan Kaluza
Faculty of Computer and Information Science Vena pot 113, 1000 Ljubljana, Slovenia, Department of Intelligent Systems Jozef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia

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 %.

Keywords: Machine Learning, eCommerce Distributed Procssing, MongoDB, Cloud

DOI:https://doi.org/10.6025/jism/2019/9/4/139-145

Full_Text PDF Download: 345 times

References:

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[2] Techcrunch, S. O’Hear, PredictionIO Raises $2.5M For Its Open Source Machine Learning Server. http://techcrunch.com/2014/07/17/predictionio/, 2014-09-05
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html, 2014-09-05
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[13] Demo e-commerce application. http://predictionio. ijs.si:8001/
[14] Basics of PredictionIO. http://docs.prediction.io/current/concepts/basics.html
[15] Dunning, T. (2014). Surprise and Coincidence. http://tdunning.blogspot.com/2008/03/surprise-andcoincidence. html, 2014-09-05

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