early results for chinese named entity recognition using conditional     random fields model, hmm and maximum entropy

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	early results for chinese named entity recognition using conditional random fields model, hmm and maximum entropy
	Feng YY; Sun L; Zhang JL
	2005
Conference Name	International Conference on Natural Language Processing and Knowledge Engineering
Source	Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05
Pages	549-552
Conference Date	OCT 30-NOV
Conference Place	Wuhan, PEOPLES R CHINA
Indexed Type	istp ; ei
Publish Place	345 E 47TH ST, NEW YORK, NY 10017 USA
Publisher	Proceedings of the 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE05)
ISBN	0-7803-9361-9
Department	Chinese Acad Sci, Inst Software, Open Syst & Chinese Informat Proc Ctr, Beijing 100080, Peoples R China.
English Abstract	Named Entity Recognition (NER) is an important step for many natural language applications, such as information extraction, text summarization, and question answering. Chinese NER has some special characteristics that make this task difficult.
Keyword	Data Structures Glossaries Information Retrieval Markov Processes Mathematical Models Pattern Recognition Text Processing
Sponsorship	IEEE, AAI, CIPSC, Chinese Assoc Artificial Intelligence, IEEE Signal Proc Soc, IEEE Beijing Sect
Language	英语
Content Type	会议论文
URI	http://ir.iscas.ac.cn/handle/311060/12564
Collection	中国科学院软件研究所
Recommended Citation GB/T 7714	Feng YY,Sun L,Zhang JL. early results for chinese named entity recognition using conditional random fields model, hmm and maximum entropy[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:Proceedings of the 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE05),2005:549-552.

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