Knowledge Mining for Project Management and Execution

Shinji Mochida

doi:10.20965/jaciii.2011.p0454

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JACIII Vol.15 No.4 pp. 454-459

doi: 10.20965/jaciii.2011.p0454

(2011)

Paper:

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Knowledge Mining for Project Management and Execution

Shinji Mochida

University of Marketing and Distribution Sciences, 3-1 Gakuen-Nishimachi, Nishiku, Kobe, Hyougo 651-2188, Japan

Received:

January 7, 2011

Accepted:

February 25, 2011

Published:

June 20, 2011

Keywords:

project management, EVM, cost, profit, loss

Abstract

Efficient project management is demanded to solve project management problems. Project success or failure depends on the skill of the project manager. A good project manager must have good knowledge on project management and growth. If knowledge is considered a judgment for effective action, the manager’s action and experience must first be registered. This paper defines knowledge as a group of low-level information and data. Such knowledge must be registered easily. Since it is difficult to find the appropriate timing for registering knowledge, this paper shows how to maximize such timing and registration for the knowledge. Knowledge is information and data for execution performance that is improvement for project management. We constructed a prototype using WEB technology to collect large amounts of knowledge for project management, but such knowledge must be registered manually and it is difficult to find the time that information should be registered on. This paper discusses how to find the best timing for registering knowledge. We tried to take into the change in progress of the project in order to get the knowledge. Earned Value Management (EVM), which is one way to manage project progress, is examined to find change in project progress, since the time that progress changes appears to be the best timing for registration. It was found that knowledge may be able to be registered automatically. It will be necessary to achieve the function to register the knowledge at the just timing in the future.

Cite this article as:

S. Mochida, “Knowledge Mining for Project Management and Execution,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.4, pp. 454-459, 2011.

Data files:

References

[1] Q. W. Fleming and J. M. Koffleman, “Earned Value Project Management,” Project Management Inst., Nihon nouritu kyoukai, 2004. (Translation)
[2] P. F. Rad andK. Itou, “PROJECT ESTIMATINGCOSTMANAGEMENT,” Seisannsei syuxtupan, 2004. (Translation)
[3] T. J. Peters and K. Oomae, “IN SERCH OF EXCELLENCE,” Eijipress Buisness Classics, 2003. (Translation)
[4] S. Mochida, “Dynamic Knowledge Collection System Using Web Technology,” J. of Biomedical Fuzzy Systems Association, Vol.5, No.1, August 2003, BMFSA, pp. 31-36, 2003.
[5] N. Kaneko, “Text for Project management,” Nihon Keizai Shimbun Inc., 2008.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] Q. W. Fleming and J. M. Koffleman, “Earned Value Project Management,” Project Management Inst., Nihon nouritu kyoukai, 2004. (Translation)

[2] [2] P. F. Rad andK. Itou, “PROJECT ESTIMATINGCOSTMANAGEMENT,” Seisannsei syuxtupan, 2004. (Translation)

[3] [3] T. J. Peters and K. Oomae, “IN SERCH OF EXCELLENCE,” Eijipress Buisness Classics, 2003. (Translation)

[4] [4] S. Mochida, “Dynamic Knowledge Collection System Using Web Technology,” J. of Biomedical Fuzzy Systems Association, Vol.5, No.1, August 2003, BMFSA, pp. 31-36, 2003.

[5] [5] N. Kaneko, “Text for Project management,” Nihon Keizai Shimbun Inc., 2008.