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Motivation

A leading handset manufacture was looking to monetize content delivery and built out a mobile video streaming service. They wanted to promote additional sales/rental of movies and wanted to tune their legacy recommendation engine running on an older version of Hadoop with Mahout. Major pain points were the speed and accuracy of their existing approach, despite having a large team of modelers within the company.

Solution

We built a machine learning model using our recommender system. In less than a week, the solution delivered a 1500x improvement in run-time and improved the accuracy of the model by 20%. The model provides an interpretable system that optimally understands user preferences.

Benefits

  • 20% improvemen t in recommendation relevance

  • 1500x execution speedup

  • Optimally understand user preferences

  • Allow for diversity in recommendation without excessive obscurity

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