A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
Research on E-commerce Consumer Behavior Prediction based on Rough Sets
2015
International Journal of u- and e- Service, Science and Technology
To solve the traditional problem of knowledge acquisition bottleneck in e-commerce, an improved algorithm of attribute reduction based on discernibility matrix is proposed. The algorithm is used to attribute reduction for e-commerce consumer behavior prediction. With rule extraction model of rough sets, the rules of e-commerce consumer behavior prediction are acquired. Practical example of consumer behavior prediction shows that the proposed approach can be handled found knowledge effectively
doi:10.14257/ijunesst.2015.8.4.08
fatcat:rkgnj22r6jh3tik7qk3tmim53q