Abstract:

To tackle with the blindness of random questions choosing for exercise and test of online learning system, this paper clusters questions by exploiting various

feature subsets and parameters based on online judge data and Kmeans. For the test data of ACM online judge system, the features of temporal fluctuations, mean of time

consumption and repeat submission rate are used to build a classification model which will be optimized based on experimental analysis of number of features and clusters. The

experimental results show that the proposed method is simple but effective, the classification results of the model are consistent with the empirical results.

Key words:  , online judge system； Kmeans； grade classification

CLC Number: 

• TP311