A Topic Model of Observing Chinese Characters
The Topic Models are a class of hierarchical statistical models for analyzing document collections and it has become one of the most used techniques in Natural Language Processing in the recent years. It assumes that each document could be expressed as a mixture of topics and each topic could be characterized by a distribution over words. In previous research 6, like in English language, Topic Models for Chinese Language use the words as observing data. In this research, we demonstrated the effectiveness of using Chinese characters as the basic units of observing data. The comparisons with those models based on Chinese words and English words are presented.
Yunkai Zhang Zengchang Qin
College of Software Beihang University Beijing,China,100191 Intelligent Computing and Machine Learning Lab School of Automation Science and Electrical Engineeri
国际会议
南京
英文
346-349
2010-08-26（万方平台首次上网日期，不代表论文的发表时间）