Scalable and Efficient Data Analytics and Mining with Lemonade

Professionals outside of the area of Computer Science have an increasing need to analyze large bodies of data. This analysis often demands high level of security and has to be done in the cloud. Ho...

[1]  Nada Lavrac,et al.  ClowdFlows: Online workflows for distributed big data mining , 2017, Future Gener. Comput. Syst..

[2]  Martin Mozina,et al.  Orange: data mining toolbox in python , 2013, J. Mach. Learn. Res..

[3]  Scott Shenker,et al.  Spark: Cluster Computing with Working Sets , 2010, HotCloud.

[4]  Clara Aguirre Hernando.  Backstage to the Panama Papers: big data analytics and collaborative journalism , 2017 .

[5]  Ian T. Foster,et al.  Ophidia: A full software stack for scientific data analytics , 2014, 2014 International Conference on High Performance Computing & Simulation (HPCS).

[6]  Ingo Mierswa,et al.  YALE: rapid prototyping for complex data mining tasks , 2006, KDD '06.

[7]  Tom White,et al.  Hadoop: The Definitive Guide , 2009 .

[8]  Neha Narkhede,et al.  Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale , 2017 .

[9]  Thorsten Meinl,et al.  KNIME - the Konstanz information miner: version 2.0 and beyond , 2009, SKDD.

[10]  Latanya Sweeney,et al.  k-Anonymity: A Model for Protecting Privacy , 2002, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[11]  Rosa M. Badia,et al.  COMP Superscalar: Bringing GRID Superscalar and GCM Together , 2008, 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (CCGRID).

[12]  Wagner Meira,et al.  Lemonade: A Scalable and Efficient Spark-Based Platform for Data Analytics , 2017, 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID).

[13]  Vijay Srinivas Agneeswaran,et al.  Paradigms for Realizing Machine Learning Algorithms , 2013, Big Data.