Data mining

Aparna Varde, Richard D. Sisson

Research output: Contribution to journalShort survey

Abstract

Data mining, which consists of finding the trends or patterns in large data sets, in order to guide decisions about future activities, is discussed. It is related to the sub-area of statistics called Exploratory Data Analysis and the sub-areas of artificial intelligence called Knowledge Discovery and Machine Learning. There are various data mining techniques such as association analysis, clustering and decision tree classification. These techniques can be applied to the materials science domain, with the goal of making estimations useful for Decision Support in the industry.

Original languageEnglish
Pages (from-to)48-49
Number of pages2
JournalHeat Treating Progress
Volume4
Issue number1
StatePublished - 1 Jan 2004

Fingerprint

Data mining
Materials science
Decision trees
Artificial intelligence
Learning systems
Statistics
Industry

Cite this

Varde, A., & Sisson, R. D. (2004). Data mining. Heat Treating Progress, 4(1), 48-49.
Varde, Aparna ; Sisson, Richard D. / Data mining. In: Heat Treating Progress. 2004 ; Vol. 4, No. 1. pp. 48-49.
@article{3e2fef8ff756440fb40c70a759f4069f,
title = "Data mining",
abstract = "Data mining, which consists of finding the trends or patterns in large data sets, in order to guide decisions about future activities, is discussed. It is related to the sub-area of statistics called Exploratory Data Analysis and the sub-areas of artificial intelligence called Knowledge Discovery and Machine Learning. There are various data mining techniques such as association analysis, clustering and decision tree classification. These techniques can be applied to the materials science domain, with the goal of making estimations useful for Decision Support in the industry.",
author = "Aparna Varde and Sisson, {Richard D.}",
year = "2004",
month = "1",
day = "1",
language = "English",
volume = "4",
pages = "48--49",
journal = "Heat Treating Progress",
issn = "1536-2558",
publisher = "ASM International",
number = "1",

}

Varde, A & Sisson, RD 2004, 'Data mining', Heat Treating Progress, vol. 4, no. 1, pp. 48-49.

Data mining. / Varde, Aparna; Sisson, Richard D.

In: Heat Treating Progress, Vol. 4, No. 1, 01.01.2004, p. 48-49.

Research output: Contribution to journalShort survey

TY - JOUR

T1 - Data mining

AU - Varde, Aparna

AU - Sisson, Richard D.

PY - 2004/1/1

Y1 - 2004/1/1

N2 - Data mining, which consists of finding the trends or patterns in large data sets, in order to guide decisions about future activities, is discussed. It is related to the sub-area of statistics called Exploratory Data Analysis and the sub-areas of artificial intelligence called Knowledge Discovery and Machine Learning. There are various data mining techniques such as association analysis, clustering and decision tree classification. These techniques can be applied to the materials science domain, with the goal of making estimations useful for Decision Support in the industry.

AB - Data mining, which consists of finding the trends or patterns in large data sets, in order to guide decisions about future activities, is discussed. It is related to the sub-area of statistics called Exploratory Data Analysis and the sub-areas of artificial intelligence called Knowledge Discovery and Machine Learning. There are various data mining techniques such as association analysis, clustering and decision tree classification. These techniques can be applied to the materials science domain, with the goal of making estimations useful for Decision Support in the industry.

UR - http://www.scopus.com/inward/record.url?scp=2942590269&partnerID=8YFLogxK

M3 - Short survey

AN - SCOPUS:2942590269

VL - 4

SP - 48

EP - 49

JO - Heat Treating Progress

JF - Heat Treating Progress

SN - 1536-2558

IS - 1

ER -

Varde A, Sisson RD. Data mining. Heat Treating Progress. 2004 Jan 1;4(1):48-49.