Introduction: recent Developments in Parallel and Distributed Data
Mining
M. Zaki, and Y. Pan. Distributed and Parallel Databases, (2002)This is an introduction to four articles about Knowledge Discovery
in Databases, KDD. It makes the statement that the key challenge
in data mining is the extraction of knowledge and insight from massive
databases. Data mining has the two primary goals of prediction and
verification. Prediction is about predicting the unknown values
of attributes of interest based on a trained model. The data mining
process is being divided into data selection, data cleansing, data
transformation, data reduction, data mining, algorithm selection,
post processing, and interpolation..
This is an introduction to four articles about Knowledge Discovery
in Databases, KDD. It makes the statement that the key challenge
in data mining is the extraction of knowledge and insight from massive
databases. Data mining has the two primary goals of prediction and
verification. Prediction is about predicting the unknown values
of attributes of interest based on a trained model. The data mining
process is being divided into data selection, data cleansing, data
transformation, data reduction, data mining, algorithm selection,
post processing, and interpolation.
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%0 Journal Article
%1 zaki02
%A Zaki, Mohammed J.
%A Pan, Yi
%D 2002
%J Distributed and Parallel Databases
%K imported
%P 123-127
%T Introduction: recent Developments in Parallel and Distributed Data
Mining
%V 11
@article{zaki02,
added-at = {2008-04-30T12:59:47.000+0200},
author = {Zaki, Mohammed J. and Pan, Yi},
biburl = {https://www.bibsonomy.org/bibtex/2cff04b9d35d6686862dc37dc56d115d6/kdubiq},
description = {KDubiq Blueprint},
groupsearch = {0},
interhash = {3ecdbbe959c9674b1eda7d670c44a0fc},
intrahash = {cff04b9d35d6686862dc37dc56d115d6},
journal = {Distributed and Parallel Databases},
keywords = {imported},
note = {This is an introduction to four articles about Knowledge Discovery
in Databases, KDD. It makes the statement that the key challenge
in data mining is the extraction of knowledge and insight from massive
databases. Data mining has the two primary goals of prediction and
verification. Prediction is about predicting the unknown values
of attributes of interest based on a trained model. The data mining
process is being divided into data selection, data cleansing, data
transformation, data reduction, data mining, algorithm selection,
post processing, and interpolation.},
pages = {123-127},
timestamp = {2008-04-30T13:00:31.000+0200},
title = {Introduction: recent Developments in Parallel and Distributed Data
Mining},
volume = 11,
year = 2002
}