Construction and Application of a Cloud Computing Based Basic Education Information Service Platform

Conventional classification method has good performance when applied to small datasets; however, their applicability to unknown data sets is weak. To serve education information services in the cloud computing (CC) environment, this study presented a cross-source education information classification model based on cloud computing technology. This work outlined mode of CC service and its mode of deployment and provided a processing method of multisource information depend on CC centre integrated with the features of information distribution in CC environment. First, function and structure of CC platform were analyzed. Second, this research provided a summary of feature extraction process of educational information utilizing technology of data mining and provided an approach for classifying educational information depend on text features by analyzing different types of educational information resources. Finally, a model for classifying cross-source academic information in a cloud computing setting was developed. The comparison of experiments proved that the approach presented in this paper has the ability of efficiently categorizing multisource educational information under CC platform. This approach outperformed other traditional categorization method of Support Vector Machine (SVM) in terms of efficiency and also accuracy.