Korean named entity recognition using HMM and CoTraining model

Namedentityrecognition isimportantinsophisticatedinformation service system such as Question Answering and Text Mining since most of the answer type and text mining unit depend on the named entitytype.Thereforewefocusonnamedentityrecognitionmodelin Korean. Koreannamed entityrecognitionisdifficultsinceeachword of named entity has not specific features such as the capitalizing feature of English. It has high dependence on the large amounts of hand-labeled data and the named entity dictionary, even though these are tedious and expensive to create. In this paper, we devise HMM based named entity recognizer to consider various context models. Furthermore, we consider weakly supervised learning technique, CoTraining,to combine labeled data and unlabeled data. Keywords :KoreanNamed Entity,HMM,Co-Training

• Type: Conference
• Year: 2003
• Where: IRAL
• Authors: Euisok Chung, Yi-Gyu Hwang, Myung-Gil Jang
• Keywords: Entity Recognizer, Information Retrieval, IRAL 2003, Mining Unit Depend, Text Mining