Ryan Swanstrom

7 Important Data Science Papers

7 important data science paper

It is back-to-school time, and here are some papers to keep you busy this school year. All the papers are free. This list is far from exhaustive, but these are some important papers in data science and big data.

Google Search

  • PageRank – This is the paper that explains the algorithm behind Google search.

Hadoop

  • MapReduce – This paper explains a programming model for processing large datasets. In particular, it is the programming model used in hadoop.
  • Google File System – Part of hadoop is HDFS. HDFS is an open-source version of the distributed file system explained in this paper.

NoSQL

These are 2 of the papers that drove/started the NoSQL debate. Each paper describes a different type of storage system intended to be massively scabable.

Machine Learning

Bonus Paper

  • Random Forests – One of the most popular machine learning techniques. It is heavily used in Kaggle competitions, even by the winners.

Are there any other papers you feel should be on the list?

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25 responses to “7 Important Data Science Papers”

  1. Arni Avatar
    Arni

    Maybe include a literature survey on neural networks? Not my field of specialty so I won’t recommend one, but I know it’s about to get red hot.

    Reply
    1. Ryan Swanstrom Avatar
      Ryan Swanstrom

      That is true. Also, a paper on random forests would be nice as well. I may have to look for best papers on those topics.

      Thanks,
      Ryan

      Reply
  2. Gurupad Hegde Avatar
    Gurupad Hegde

    @Ryan: Link to Random Forest Paper: http://oz.berkeley.edu/~breiman/randomforest2001.pdf

    Reply
    1. Ryan Swanstrom Avatar
      Ryan Swanstrom

      Thank you very much for the link. That would the correct random forest paper to add. I have added it to the list.

      Ryan

      Reply
  3. [repost ]7 Important Data Science Papers » New IT Farmer

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  4. richarddunks Avatar
    richarddunks

    Reblogged this on Datapolitan and commented:
    Great list of resources, though I’d add E.F. Codd’s seminal “A Relational Model of Data for Large Shared Data Banks”: http://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf

    Reply
  5. Subhadeep Paul Avatar
    Subhadeep Paul

    Another paper on MapReduce that helped me a lot in writing algorithms in MapReduce framework is this one http://machinelearning.wustl.edu/mlpapers/paper_files/NIPS2006_725.pdf
    and to handle large data sets, Breiman’s Pasting small votes paper
    http://sci2s.ugr.es/keel/pdf/algorithm/articulo/1999-ML-Breiman-Pasting%20Small%20Votes%20for%20Classification%20in%20Large%20Databases%20and%20On-Line.pdf

    Reply
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  8. garyshort Avatar
    garyshort

    Reblogged this on Gary Short.

    Reply
    1. Ryan Swanstrom Avatar
      Ryan Swanstrom

      thanks for reblogging

      Reply
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  10. charles Avatar
    charles

    great resource list. any papers on statistics as it changes to handle larger datasets?

    Reply
    1. Ryan Swanstrom Avatar
      Ryan Swanstrom

      That is a great idea. I have not looked for any papers on that topic. If I find any, I will post it to the blog. Thanks for the comment.

      Ryan

      Reply
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  12. Kartik Avatar
    Kartik

    Nice list !! Also, consider Amazon.com recommendations http://www.win.tue.nl/~laroyo/2L340/resources/Amazon-Recommendations.pdf

    Reply
    1. Ryan Swanstrom Avatar
      Ryan Swanstrom

      Oh, that is a good. I have not seen it before. Thanks for the recommendation on the recommendation paper.

      Ryan

      Reply
    2. Sharad Avatar
      Sharad

      Thanks for the awesome list, Ryan!

      Thanks for sharing the Amazon recommendations PDF, Kartik! Unfortunately, the link doesn’t seem to work any longer. Can you re-post it please?

      Reply
      1. Ryan Swanstrom Avatar
        Ryan Swanstrom

        I believe this is the paper in reference. https://www.cs.umd.edu/~samir/498/Amazon-Recommendations.pdf

    3. alltumdata Avatar
      alltumdata

      Thanks for sharing the list or paper, Ryan!

      Thanks for sharing the Amazon recommendations PDF, Kartik!
      Unfortunately, the link doesn’t seem to work anymore. Can you please re-post it?

      Reply
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