Applying machine learning to identify Chinese discourse markers

With their high occurrence rates in argumentative Chinese texts, discourse markers play a significant role in the automatic processing of these kinds of Chinese texts, such as automatic summarization. The paper reports on an effort in applying machine learning to identify discourse markers in Chinese. We have processed 80 Chinese texts from which we have selected subsets for data training and data testing. We used C4.5 in our experiments and obtained accuracies of the order of 80%. Accuracies obtained by neural network are a bit worse than that of C4.5. We also interpret and analyze our experimental results in the linguistic perspective.