Title :
Biclustering using Spark-MapReduce
Author :
Sarazin, Tugdual ; Lebbah, Mustapha ; Azzag, Hanane
Author_Institution :
LIPN, Univ. of Paris, Villetaneuse, France
Abstract :
Biclustering approaches are more complex compared to the traditional clustering particularly those requiring large dataset and Mapreduce platforms. We propose a new approach of biclustering based on popular self-organizing maps, which is one of the famous unsupervised learning algorithms. We have designed scalable implementations of the new topological biclustering algorithm using MapReduce with the Spark platform.
Keywords :
parallel programming; pattern clustering; unsupervised learning; Spark-MapReduce platform; large-datasets; self-organizing maps; topological biclustering algorithm; unsupervised learning algorithms; Algorithm design and analysis; Clustering algorithms; Data mining; Distributed databases; Prototypes; Sparks; Vectors; Biclustering; Map-Reduce Spark; Self-organizing Map;
Conference_Titel :
Big Data (Big Data), 2014 IEEE International Conference on
Conference_Location :
Washington, DC
DOI :
10.1109/BigData.2014.7004493
