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Working Paper IS-02-02Intelligent Assistance for the Data Mining Process:

By Abraham Bernstein and Shawndra HillFoster Provost, Abraham Bernstein, Foster Provost and Shawndra Hill

Abstract

A data mining (DM) process involves multiple stages. A simple, but typical, process might include preprocessing data, applying a data-mining algorithm, and postprocessing the mining results. There are many possible choices for each stage, and only some combinations are valid. Because of the large space and non-trivial interactions, both novices and data-mining specialists need assistance in composing and selecting DM processes. We present the concept of Intelligent Discovery Assistants (IDAs), which provide users with (i) systematic enumerations of valid DM processes, in order that important, potentially fruitful options are not overlooked, and (ii) effective rankings of these valid processes by different criteria, to facilitate the choice of DM processes to execute. We use a prototype to show that an IDA can indeed provide useful enumerations and effective rankings. We discuss how an IDA is an important tool for knowledge sharing among a team of data miners. Finally, we illustrate all the claims with a comprehensive demonstration using a more involved process and data from the 1998 KDDCUP competition

Topics: An Ontology-based Approach
Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.195.835
Provided by: CiteSeerX
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