@INCOLLECTION{Klusch_03b,
    AUTHOR      = {M. Klusch and S. Lodi and G. L. Moro},
    TITLE       = {{Agent-Based Distributed Data Mining: The KDEC Scheme}},
    BOOKTITLE   = {{Intelligent Information Agents: The AgentLink Perspective}},
    PUBLISHER   = {Springer},
    YEAR        = {2003},
    EDITOR      = {},
    PAGES       = {104-122},
    ORGANIZATION= {},
    ADDRESS     = {},
    MONTH       = {July},
    VOLUME      = {},
    NUMBER      = {},
    SERIES      = {LNAI 2586},
    NOTE        = {},
    KEY         = {},
    KEYWORDS    = {},
    ISBN        = {},
    URL         = {http://www.ingce.unibo.it/~gmoro/},
    ABSTRACT    = {One key aspect of exploiting the huge amount of autonomous and heterogeneous data
               sources in the Internet is not only how to retrieve, collect and integrate relevant
               information but to discover previously unknown, implicit and valuable knowledge. In
               recent years several approaches to distributed data mining and knowledge discovery
               have been developed, but only a few of them make use of intelligent agents. This
               paper is intended to argue for the potential added value of using agent technology
               in the domain of knowledge discovery. We briefly review and classify existing
               approaches to agent-based distributed data mining, propose a novel approach to
               distributed data clustering based on density estimation, and discuss issues of its
               agent-oriented implementation.
                   },
}