DocumentCode
3239120
Title
The study on web data mining based on belief rough set classification
Author
Gui-ling, Li
Author_Institution
Comput. Eng. Coll., Siping Prof. Coll., Siping, China
fYear
2011
fDate
27-29 May 2011
Firstpage
673
Lastpage
677
Abstract
In this paper, a new approach of classification system based on rough sets named BRSC have been applied to generate a classification model from uncertain data consisting of web usage. The uncertainty appears only in decision attributes and is handled by the TBM, one interpretation of the belief function theory. The feature selection step used to construct the BRSC is based on the calculation of dynamic core to extract more relevant and stable features for the classification process. In experimentations, three evaluation criteria have been chosen to judge the performance of the BRSC applied to the web usage mining dataset.
Keywords
Internet; belief networks; data mining; feature extraction; pattern classification; performance evaluation; rough set theory; uncertainty handling; BRSC; TBM; Web data mining; Web usage; belief function theory; belief rough set classification; decision attribute; feature extraction; feature selection; performance evaluation; uncertainty handling; Approximation methods; Complexity theory; Databases; Hair; Noise measurement; Rough sets; Uncertainty; Data Mining; Rough Set; Web;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
Conference_Location
Xi´an
Print_ISBN
978-1-61284-485-5
Type
conf
DOI
10.1109/ICCSN.2011.6014660
Filename
6014660
Link To Document