Data mining of project management data: An analysis of applied research studies

Gurdal Ertek; Murat Tunç; Allan Zhang; Omer Tanrikulu; Sobhan Asian

doi:10.1145/3176653.3176714

Data mining of project management data: An analysis of applied research studies

Gurdal Ertek, Murat Tunç, Allan Zhang, Omer Tanrikulu, Sobhan Asian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

Data collected and generated through and posterior to projects, such as data residing in project management software and post-project review documents, can be a major source of actionable insights and competitive advantage. This paper presents a rigorous methodological analysis of the applied research published in academic literature, on the application of data mining (DM) for project management (PM). The objective of the paper is to provide a comprehensive analysis and discussion of where and how data mining is applied for project management data and to provide practical insights for future research in the field.

Original language	English
Title of host publication	Proceedings of the 2017 International Conference on Information Technology (ICIT)
Place of Publication	Boston, MA
Publisher	ACM
Pages	35-41
DOIs	https://doi.org/10.1145/3176653.3176714
Publication status	Published - 2017
Externally published	Yes

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10.1145/3176653.3176714

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title = "Data mining of project management data: An analysis of applied research studies",

abstract = "Data collected and generated through and posterior to projects, such as data residing in project management software and post-project review documents, can be a major source of actionable insights and competitive advantage. This paper presents a rigorous methodological analysis of the applied research published in academic literature, on the application of data mining (DM) for project management (PM). The objective of the paper is to provide a comprehensive analysis and discussion of where and how data mining is applied for project management data and to provide practical insights for future research in the field.",

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year = "2017",

doi = "10.1145/3176653.3176714",

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AU - Tunç, Murat

AU - Zhang, Allan

AU - Tanrikulu, Omer

AU - Asian, Sobhan

PY - 2017

Y1 - 2017

N2 - Data collected and generated through and posterior to projects, such as data residing in project management software and post-project review documents, can be a major source of actionable insights and competitive advantage. This paper presents a rigorous methodological analysis of the applied research published in academic literature, on the application of data mining (DM) for project management (PM). The objective of the paper is to provide a comprehensive analysis and discussion of where and how data mining is applied for project management data and to provide practical insights for future research in the field.

AB - Data collected and generated through and posterior to projects, such as data residing in project management software and post-project review documents, can be a major source of actionable insights and competitive advantage. This paper presents a rigorous methodological analysis of the applied research published in academic literature, on the application of data mining (DM) for project management (PM). The objective of the paper is to provide a comprehensive analysis and discussion of where and how data mining is applied for project management data and to provide practical insights for future research in the field.

U2 - 10.1145/3176653.3176714

DO - 10.1145/3176653.3176714

M3 - Conference contribution

SP - 35

EP - 41

BT - Proceedings of the 2017 International Conference on Information Technology (ICIT)

PB - ACM

CY - Boston, MA

ER -

Data mining of project management data: An analysis of applied research studies

Abstract

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