Hadoop-based Movie Recommendation Engine: A Comparison of the Apriori Algorithm vs. the k-means Method

Hadoop-based Movie Recommendation Engine: A Comparison of the Apriori Algorithm vs. the k-means Method

In this study, our data scientist compares two approaches for implementing a Hadoop-based movie recommendation engine. Download the document to learn how generating association rules differs from clustering data and explore three ways to optimize the quality of movie recommendations.

Key take-aways:

  • Get a comparative table of Apriori vs. k-means for a movie recommendation engine
  • Discover 3 ways to speed up processing and decrease data size when working with big data
  • Find out how to pre-process data for maximum efficiency when using the Apriori and k-means algorithms with the MapReduce paradigm
  • Explore 3 ways to improve the quality of search recommendations based on association rules
  • Get an overview of 4 most popular data processing algorithms for building association rules
  • View 12 diagrams that feature real-life recommendations produced by both Apriori and k-means

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