Semirings, automata, languages
Semirings, automata, languages
Rational series and their languages
Rational series and their languages
A stochastic finite-state word-segmentation algorithm for Chinese
Computational Linguistics
A design principles of a weighted finite-state transducer library
Theoretical Computer Science - Special issue on implementing automata
Finite-state transducers in language and speech processing
Computational Linguistics
A novel use of statistical parsing to extract information from text
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Partial parsing via finite-state cascades
Natural Language Engineering
A stochastic finite-state word-segmentation algorithm for Chinese
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Finite-state transducer cascades to extract named entities in texts
Theoretical Computer Science - Implementation and application automata
More accurate tests for the statistical significance of result differences
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
ICML '04 Proceedings of the twenty-first international conference on Machine learning
HHMM-based Chinese lexical analyzer ICTCLAS
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
A maximum entropy Chinese character-based parser
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Discriminative Reranking for Natural Language Parsing
Computational Linguistics
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Composition of conditional random fields for transfer learning
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
A hybrid approach to word segmentation and POS tagging
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
A dual-layer CRFs based joint decoding method for cascaded segmentation and labeling tasks
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Jointly labeling multiple sequences: a factorial HMM approach
ACLstudent '05 Proceedings of the ACL Student Research Workshop
Joint parsing and semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
The integration of syntactic parsing and semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
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This paper introduces an approach which jointly performs a cascade of segmentation and labeling subtasks for Chinese lexical analysis, including word segmentation, named entity recognition and part-of-speech tagging. Unlike the traditional pipeline manner, the cascaded subtasks are conducted in a single step simultaneously, therefore error propagation could be avoided and the information could be shared among multi-level subtasks. In this approach, Weighted Finite State Transducers (WFSTs) are adopted. Within the unified framework of WFSTs, the models for each subtask are represented and then combined into a single one. Thereby, through one-pass decoding the joint optimal outputs for multi-level processes will be reached. The experimental results show the effectiveness of the presented joint processing approach, which significantly outperforms the traditional method in pipeline style.