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A proposed data mining methodology and its application to industrial engineering
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A proposed data mining methodology and its application to industrial engineering

Author: Jose Solarte
Publisher: 2002.
Edition/Format: eBook : Document : Thesis/dissertation : Manuscript : English
Summary:
Data mining is the process of discovering correlations, patterns, trends or relationships by searching through a large amount of data stored in repositories, corporate databases, and data warehouses. Industrial engineering is a broad field and has many tools and techniques in its problem-solving arsenal. The purpose of this study is to improve the effectiveness of industrial engineering solutions through the  Read more...
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Details

Material Type: Document, Thesis/dissertation, Manuscript, Internet resource
Document Type: Internet Resource, Computer File, Archival Material
All Authors / Contributors: Jose Solarte
OCLC Number: 50727749
Notes: Title from title page screen (viewed on Sept. 25, 2002). Thesis advisor: Denise F. Jackson. Document formatted into pages (viii, 93 p. : ill. (some col.)). Vita.
Details: Mode of access: World Wide Web.
Responsibility: Jose Solarte.

Abstract:

Data mining is the process of discovering correlations, patterns, trends or relationships by searching through a large amount of data stored in repositories, corporate databases, and data warehouses. Industrial engineering is a broad field and has many tools and techniques in its problem-solving arsenal. The purpose of this study is to improve the effectiveness of industrial engineering solutions through the application of data mining. To achieve this objective, an adaptation of the engineering design process is used to develop a methodology for effective application of data mining to databases and data repositories specifically designed for industrial engineering operations. This paper concludes by describing some of the advantages and disadvantages of the application of data mining techniques and tools to industrial engineering; it mentions some possible problems or issues in its implementation; and finally, it provides recommendations for future research in the application of data mining to facilitate decisions relevant to industrial engineering.

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