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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)
With the advent and popularity of e-commerce and clothing image-sharing websites, clothing image search and annotation become active research topics in recent years. Clothing image annotation is a challenging task due to large variations in clothing appearance, human body pose and background. In this paper, we explore part-based clothing image annotation in(More)
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