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Automated Support for Model Selectio...

Missakian, Mario Sarkis.

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Automated Support for Model Selection Using Analytic Hierarchy Process.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Automated Support for Model Selection Using Analytic Hierarchy Process./
Author:	Missakian, Mario Sarkis.
Description:	218 p.
Notes:	Source: Dissertation Abstracts International, Volume: 72-07, Section: B, page: .
Contained By:	Dissertation Abstracts International72-07B.
Subject:	Information Technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3454450
ISBN:	9781124638188

Automated Support for Model Selection Using Analytic Hierarchy Process.
Missakian, Mario Sarkis.

Automated Support for Model Selection Using Analytic Hierarchy Process. - 218 p.

Source: Dissertation Abstracts International, Volume: 72-07, Section: B, page: .

Thesis (Ph.D.)--Nova Southeastern University, 2011.

Providing automated support for model selection is a significant research challenge in model management. Organizations maintain vast growing repositories of analytical models, typically in the form of spreadsheets. Effective reuse of these models could result in significant cost savings and improvements in productivity. However, in practice, model reuse is severely limited by two main challenges: (1) lack of relevant information about the models maintained in the repository, and (2) lack of end user knowledge that prevents them from selecting appropriate models for a given problem solving task.

ISBN: 9781124638188Subjects--Topical Terms:

1030799
Information Technology.

Automated Support for Model Selection Using Analytic Hierarchy Process.
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020 $a 9781124638188
035 $a (UMI)AAI3454450
035 $a AAI3454450
040 $a UMI $c UMI
100 1 $a Missakian, Mario Sarkis. $3 1680813
245 1 0 $a Automated Support for Model Selection Using Analytic Hierarchy Process.
300 $a 218 p.
500 $a Source: Dissertation Abstracts International, Volume: 72-07, Section: B, page: .
500 $a Adviser: Sumitra Mukherjee.
502 $a Thesis (Ph.D.)--Nova Southeastern University, 2011.
520 $a Providing automated support for model selection is a significant research challenge in model management. Organizations maintain vast growing repositories of analytical models, typically in the form of spreadsheets. Effective reuse of these models could result in significant cost savings and improvements in productivity. However, in practice, model reuse is severely limited by two main challenges: (1) lack of relevant information about the models maintained in the repository, and (2) lack of end user knowledge that prevents them from selecting appropriate models for a given problem solving task.
520 $a This study built on the existing model management literature to address these research challenges. First, this research captured the relevant meta-information about the models. Next, it identified the features based on which models are selected. Finally, it used Analytic Hierarchy Process (AHP) to select the most appropriate model for any specified problem. AHP is an established method for multi-criteria decision-making that is suitable for the model selection task. To evaluate the proposed method for automated model selection, this study developed a simulated prototype system that implemented this method and tested it in two realistic end-user model selection scenarios based on previously benchmarked test problems.
590 $a School code: 1191.
650 4 $a Information Technology. $3 1030799
650 4 $a Information Science. $3 1017528
650 4 $a Computer Science. $3 626642
690 $a 0489
690 $a 0723
690 $a 0984
710 2 $a Nova Southeastern University. $b Information Systems (DISS). $3 1023901
773 0 $t Dissertation Abstracts International $g 72-07B.
790 1 0 $a Mukherjee, Sumitra, $e advisor
790 1 0 $a Cohen, Maxine $e committee member
790 1 0 $a Sun, Junping $e committee member
790 $a 1191
791 $a Ph.D.
792 $a 2011
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3454450