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Parallelized Online Matrix Factorization for Collaborative Filtering using Stochastic Gradient Descent

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Authors: Chris Johnson, Alex Tang, Muqeet Ali

CollabStream implements parallelized online matrix factorization using stochastic gradient descent in the case of online streaming data.  CollabStream utilizes the Storm parallelization framework developed by Natahn Marz and available at https://github.com/nathanmarz/storm.  For more information on the algorithm used by CollabStream please see the full report found at https://github.com/MrChrisJohnson/CollabStream.   

To run:
1. Go to the directory where you cloned the project.
2. mvn compile
3. mvn package
4. Take the jar with dependencies from the target folder (e.g., name.jar)
5. run on Hadoop cluster using:
   hadoop jar name.jar comparison.dsgd.DSGDMain inputPath outputPath numReducers
      where inputPath refers to the path of the train and test data, outputPath refers to where the RMSE and the factor matrices are outputted.  
	   

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Parallelized Online Matrix Factorization for Collaborative Filtering using Stochastic Gradient Descent

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