Learn More
This paper presents a new Chinese chunking method based on maximum entropy Markov models. We firstly present two types of Chinese chunking specifications and data sets, based on which the chunking models are applied. Then we describe the hidden Markov chunking model and maximum entropy chunking model. Based on our analysis of the two models, we propose a(More)
In response to the growing requirements of traffic classification for increasing complex network environment, this paper introduces a hybrid method for network traffic classification. By combining port-based, signature string matching, regular expression matching and machine learning methods, our method can achieve high speed and accurate traffic(More)
This paper briefly describes our system in The Fourth SIGHAN Bakeoff. Discriminative models including maximum entropy model and conditional random fields are utilized in Chinese word segmentation and named entity recognition with different tag sets and features. Transformation-based learning model is used in part-of-speech tagging. Evaluation shows that our(More)
  • 1