DocumentCode
2296902
Title
Notice of Retraction
A Model for Selecting IT Project Based on Multi-Granularity Linguistic Assessment Information
Author
Guo Jian ; Jia Chuang-liang ; Lin Ze-fu
Author_Institution
Sch. of Manage. Sci. & Eng., Central Univ. of Finance & Econ., Beijing, China
Volume
3
fYear
2010
fDate
6-7 March 2010
Firstpage
381
Lastpage
384
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, an approach based on multi-granularity linguistic assessment information is used to select IT project. Firstly, the expert linguistic assessment information is represented in the form of 2-tuple. Secondly, the basic linguistic term set is chosen from multi-granularity linguistic term sets. Then, based on the 2-tuple order weighted averaging (TOWA) and other aggregation operator, the experts´ preference information is aggregated into the group preference information and the most desirable IT project is selected. Finally, a numerical example is given to illustrate the effectiveness of the proposed approach.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, an approach based on multi-granularity linguistic assessment information is used to select IT project. Firstly, the expert linguistic assessment information is represented in the form of 2-tuple. Secondly, the basic linguistic term set is chosen from multi-granularity linguistic term sets. Then, based on the 2-tuple order weighted averaging (TOWA) and other aggregation operator, the experts´ preference information is aggregated into the group preference information and the most desirable IT project is selected. Finally, a numerical example is given to illustrate the effectiveness of the proposed approach.
Keywords
computational linguistics; project management; software development management; 2-tuple order weighted averaging; IT project; aggregation operator; basic linguistic term set; expert linguistic assessment information; group preference information; multigranularity linguistic assessment information; multigranularity linguistic term sets; Computational modeling; Computer science; Computer science education; Decision making; Educational technology; Financial management; Information processing; Investments; Project management; Technology management; 2-tuple linguistic representation; IT project selection; Multi-granularity; group decision-making;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6388-6
Type
conf
DOI
10.1109/ETCS.2010.176
Filename
5459664
Link To Document