A stochastic finite-state word-segmentation algorithm for Chinese
Computational Linguistics
An Algorithm that Learns What‘s in a Name
Machine Learning - Special issue on natural language learning
Lexical semantics and automatic hypertext construction
ACM Computing Surveys (CSUR)
A maximum entropy approach to named entity recognition
A maximum entropy approach to named entity recognition
A trainable rule-based algorithm for word segmentation
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
BEN: description of the PLUM system as used for MUC-6
MUC6 '95 Proceedings of the 6th conference on Message understanding
SRI International FASTUS system: MUC-6 test results and analysis
MUC6 '95 Proceedings of the 6th conference on Message understanding
Japanese named entity recognition based on a simple rule generator and decision tree learning
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Building semantic perceptron net for topic spotting
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
CRYSTAL inducing a conceptual dictionary
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Automatically generating extraction patterns from untagged text
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
VideoQA: question answering on news video
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
A bootstrapping approach to annotating large image collection
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
Extracting pronunciation-translated names from Chinese texts using bootstrapping approach
SIGHAN '02 Proceedings of the first SIGHAN workshop on Chinese language processing - Volume 18
Chinese Named Entity Recognition combining a statistical model with human knowledge
MultiNER '03 Proceedings of the ACL 2003 workshop on Multilingual and mixed-language named entity recognition - Volume 15
Cascading use of soft and hard matching pattern rules for weakly supervised information extraction
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Chinese named entity recognition based on multiple features
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Fuzzy pattern rule induction for information extraction
ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
A two-view cotraining rule induction system for information extraction
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
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Named entity (NE) extraction in Chinese is very difficult task because of the flexibility in the language structure and uncertainty in word segmentation. It is equivalent to relation and information extraction problems in English. This paper presents a hybrid rule induction approach to extract NEs in Chinese. The method induces rules and names and their context, and generalizes these rules using linguistic lexical chaining. In order to handle the ambiguities and other contextual problems peculiar to Chinese, we supplement the basic method with other approaches such as the default-exception tree and decision tree. We tested our method on the MET2 test set and the method has been found to out-perform all reported methods with an overall F1 measure of over 91%.