Intelligent Assistance for the Data Mining Process: an Ontology-Based Approach
University of Zurich
New York University (NYU) - Leonard N. Stern School of Business
New York University
NYU Working Paper No. 2451/14146
A data mining (DM) process involves multiple stages. A simple, but typical, process might includepreprocessing data, applying a data-mining algorithm, and postprocessing the mining results. Thereare many possible choices for each stage, and only some combinations are valid. Because of thelarge space and non-trivial interactions, both novices and data-mining specialists need assistance incomposing 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 thatimportant, potentially fruitful options are not overlooked, and (ii) effective rankings of these validprocesses by different criteria, to facilitate the choice of DM processes to execute. We use a prototypeto show that an IDA can indeed provide useful enumerations and effective rankings. We discusshow 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 anddata from the 1998 KDDCUP competition.
Number of Pages in PDF File: 41
Keywords: Data mining, data-mining process, intelligent assistants, knowledge discoveryworking papers series
Date posted: October 13, 2008
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