Weka4WS: A WSRF-Enabled Weka Toolkit for Distributed Data Mining on Grids

  • Domenico Talia
  • Paolo Trunfio
  • Oreste Verta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3721)


This paper presents Weka4WS, a framework that extends the Weka toolkit for supporting distributed data mining on Grid environments. Weka4WS adopts the emerging Web Services Resource Framework (WSRF) for accessing remote data mining algorithms and managing distributed computations. The Weka4WS user interface is a modified Weka Explorer environment that supports the execution of both local and remote data mining tasks. On every computing node, a WSRF-compliant Web Service is used to expose all the data mining algorithms provided by the Weka library. The paper describes the design and the implementation of Weka4WS using a first release of the WSRF library. To evaluate the efficiency of the proposed system, a performance analysis of Weka4WS for executing distributed data mining tasks in different network scenarios is presented.


Execution Time Data Mining Association Rule Computing Node Total Execution Time 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Domenico Talia
    • 1
  • Paolo Trunfio
    • 1
  • Oreste Verta
    • 1
  1. 1.DEISUniversity of CalabriaRendeItaly

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