Title :
The study on web data mining based on belief rough set classification
Author_Institution :
Comput. Eng. Coll., Siping Prof. Coll., Siping, China
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;
Conference_Titel :
Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-61284-485-5
DOI :
10.1109/ICCSN.2011.6014660