DocumentCode
2834799
Title
Notice of Retraction
A Packet Classification Algorithm Base Rule Entropy
Author
Shanxiong Chen ; Xianping Yu ; Maoling Pen ; Aiming Huang
Author_Institution
Coll. of Comput. & Inf. Sci., Southwest Univ., Chongqing, China
fYear
2009
fDate
19-20 Dec. 2009
Firstpage
1
Lastpage
4
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.
Firstly, by preprocessing classification rule, we account distinct outlier attributes subspace of the rules about classification rules attributes, then it uses attribute weight vector to calculate weighted distance; secondly, it analyzes subspace outlier influence factor of weighted neighborhood area; finally, we creates frequent matching Sub-Set by comparing with subspace outlier influence factor. Following packet that needs to be matched is restricted within narrow area which is constituted by the Sub-Set, so packet matching is more efficient than before.
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.
Firstly, by preprocessing classification rule, we account distinct outlier attributes subspace of the rules about classification rules attributes, then it uses attribute weight vector to calculate weighted distance; secondly, it analyzes subspace outlier influence factor of weighted neighborhood area; finally, we creates frequent matching Sub-Set by comparing with subspace outlier influence factor. Following packet that needs to be matched is restricted within narrow area which is constituted by the Sub-Set, so packet matching is more efficient than before.
Keywords
entropy; pattern classification; probability; attribute weight vector; classification rule; outlier influence factor; packet matching; rule entropy; sub-set match; Algorithm design and analysis; Cities and towns; Classification algorithms; Educational institutions; Filtering; Frequency; Information analysis; Information entropy; Information science; Quality of service;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4994-1
Type
conf
DOI
10.1109/ICIECS.2009.5364358
Filename
5364358
Link To Document