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Recovery: A novel data mining approa...

Liu, Dong.

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Recovery: A novel data mining approach from mining engineering perspectives.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Recovery: A novel data mining approach from mining engineering perspectives./
Author:	Liu, Dong.
Description:	367 p.
Notes:	Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5590.
Contained By:	Dissertation Abstracts International66-10B.
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3193805
ISBN:	9780542381393

Recovery: A novel data mining approach from mining engineering perspectives.
Liu, Dong.

Recovery: A novel data mining approach from mining engineering perspectives. - 367 p.

Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5590.

Thesis (Ph.D.)--The University of Alabama, 2005.

The amount of data produced is growing explosively and demands efficient ways to mine the information. As a highly interdisciplinary field, data mining derives ideas and methodologies from many disciplines. Mineral mining terminologies have been widely used in data mining products, company names, and websites. The metaphorical relationship implies strong links between data mining and mineral mining. However, an in-depth and systematic study between these two fields has been lacking.

ISBN: 9780542381393Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Recovery: A novel data mining approach from mining engineering perspectives.
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100 1 $a Liu, Dong. $3 1909292
245 1 0 $a Recovery: A novel data mining approach from mining engineering perspectives.
300 $a 367 p.
500 $a Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5590.
500 $a Chairman: William A. Stapleton.
502 $a Thesis (Ph.D.)--The University of Alabama, 2005.
520 $a The amount of data produced is growing explosively and demands efficient ways to mine the information. As a highly interdisciplinary field, data mining derives ideas and methodologies from many disciplines. Mineral mining terminologies have been widely used in data mining products, company names, and websites. The metaphorical relationship implies strong links between data mining and mineral mining. However, an in-depth and systematic study between these two fields has been lacking.
520 $a This research endeavors to introduce mineral mining into data mining. The analogy of data mining and mineral mining is presented from the macroscopic to the microscopic. A Recovery problem stemming from the interdisciplinary study is found in the database environment. The nature and uniqueness of the Recovery theory is examined in the research. Recovery metrics are derived from mineral mining engineering. An example of the application of Recovery theory is provided in the form of a university donation campaign. All steps of the process, pre-Recovery mining, Recovery mining, and post-Recovery mining, are analyzed in this example.
520 $a The preliminary study of Recovery theory reveals that mineral mining can provide data mining real techniques for implementation. Recovery theory strives to maximize information retrieval from the entire resource and the integrated reserve in a cost-efficient fashion. It reflects many business demands.
590 $a School code: 0004.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Computer Science. $3 626642
650 4 $a Engineering, Mining. $3 1035560
690 $a 0544
690 $a 0984
690 $a 0551
710 2 0 $a The University of Alabama. $3 1019361
773 0 $t Dissertation Abstracts International $g 66-10B.
790 1 0 $a Stapleton, William A., $e advisor
790 $a 0004
791 $a Ph.D.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3193805