DocumentCode
518952
Title
Notice of Retraction
Customer clustering analysis: A new algorithm based on swarm intelligence
Author
Weihui Dai ; Duo Xu
Author_Institution
Sch. of Manage., Fudan Univ., Shanghai, China
fYear
2010
fDate
11-13 May 2010
Firstpage
599
Lastpage
603
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.
Clustering analysis is one of the fundamental technologies for conducting customer oriented services and the services management. Due to the continuously changes in the composition, need, experience and interest of customers, it may be difficult in refining stable and consistent aggregations of those customers. This paper presented a new algorithm for customer clustering analysis. It was originally inspired from the swarm intelligence of ant colony, and exhibited the excellent ability in adaptive clustering analysis. Applied by this new algorithm, an adaptive recommendation system for mobile TV was designed to provide the customer oriented programming dynamically and adaptively.
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.
Clustering analysis is one of the fundamental technologies for conducting customer oriented services and the services management. Due to the continuously changes in the composition, need, experience and interest of customers, it may be difficult in refining stable and consistent aggregations of those customers. This paper presented a new algorithm for customer clustering analysis. It was originally inspired from the swarm intelligence of ant colony, and exhibited the excellent ability in adaptive clustering analysis. Applied by this new algorithm, an adaptive recommendation system for mobile TV was designed to provide the customer oriented programming dynamically and adaptively.
Keywords
customer services; mobile computing; mobile television; optimisation; pattern clustering; recommender systems; adaptive recommendation system; ant colony; customer clustering analysis; customer oriented programming; customer oriented services; mobile TV; services management; swarm intelligence; Adaptive systems; Algorithm design and analysis; Clustering algorithms; Data analysis; Dynamic programming; Intelligent networks; Mobile TV; Particle swarm optimization; Space technology; Technology management; clustering; customer analysis; data mining; swarm intelligence;
fLanguage
English
Publisher
ieee
Conference_Titel
New Trends in Information Science and Service Science (NISS), 2010 4th International Conference on
Conference_Location
Gyeongju
Print_ISBN
978-1-4244-6982-6
Type
conf
Filename
5488548
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