An Architecture for Collaborative Data Mining

نویسندگان

  • Francisco Correia
  • Rui Camacho
  • João Correia Lopes
چکیده

Collaborative Data Mining (CDM) develops techniques to solve complex problems of data analysis requiring sets of experts in different domains that may be geographically separate. An important issue in CDM is the sharing of experience among the different experts. In this paper we report on a framework that enables users with different expertise to perform data analysis activities and profit, in a collaborative fashion, from expertise and results of other researchers. The collaborative process is supported by web services that seek for relevant knowledge available among the collaborative web sites. We have successfully designed and deployed a prototype for collaborative Data Mining in domains of Molecular Biology and Chemoinformatics.

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تاریخ انتشار 2010