Shallow Parsing with Conditional Random Fields
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[1] J. M. Hammersley,et al. Markov fields on finite graphs and lattices , 1971 .
[2] J. Darroch,et al. Generalized Iterative Scaling for Log-Linear Models , 1972 .
[3] Stephen Cox,et al. Some statistical issues in the comparison of speech recognition algorithms , 1989, International Conference on Acoustics, Speech, and Signal Processing,.
[4] Steven Abney,et al. Parsing By Chunks , 1991 .
[5] Julian M. Kupiec,et al. Robust part-of-speech tagging using a hidden Markov model , 1992 .
[6] J. Shewchuk. An Introduction to the Conjugate Gradient Method Without the Agonizing Pain , 1994 .
[7] Eric Brill,et al. Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging , 1995, CL.
[8] Mitchell P. Marcus,et al. Text Chunking using Transformation-Based Learning , 1995, VLC@ACL.
[9] Adwait Ratnaparkhi,et al. A Maximum Entropy Model for Part-Of-Speech Tagging , 1996, EMNLP.
[10] Adam L. Berger,et al. A Maximum Entropy Approach to Natural Language Processing , 1996, CL.
[11] Adwait Ratnaparkhi,et al. A Linear Observed Time Statistical Parser Based on Maximum Entropy Models , 1997, EMNLP.
[12] John D. Lafferty,et al. Inducing Features of Random Fields , 1995, IEEE Trans. Pattern Anal. Mach. Intell..
[13] Stanley F. Chen,et al. A Gaussian Prior for Smoothing Maximum Entropy Models , 1999 .
[14] Yoram Singer,et al. Boosting Applied to Tagging and PP Attachment , 1999, EMNLP.
[15] Andrew McCallum,et al. Information Extraction with HMM Structures Learned by Stochastic Optimization , 2000, AAAI/IAAI.
[16] Dan Roth,et al. The Use of Classifiers in Sequential Inference , 2001, NIPS.
[17] Alexander S. Yeh,et al. More accurate tests for the statistical significance of result differences , 2000, COLING.
[18] Sabine Buchholz,et al. Introduction to the CoNLL-2000 Shared Task Chunking , 2000, CoNLL/LLL.
[19] Andrew McCallum,et al. Maximum Entropy Markov Models for Information Extraction and Segmentation , 2000, ICML.
[20] Yuji Matsumoto,et al. Chunking with Support Vector Machines , 2001, NAACL.
[21] D K Smith,et al. Numerical Optimization , 2001, J. Oper. Res. Soc..
[22] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[23] Mark Johnson,et al. Dynamic programming for parsing and estimation of stochastic unification-based grammars , 2002, ACL.
[24] Tong Zhang,et al. Text Chunking based on a Generalization of Winnow , 2002, J. Mach. Learn. Res..
[25] Michael Collins,et al. Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms , 2002, EMNLP.
[26] Mark Johnson,et al. Parsing the Wall Street Journal using a Lexical-Functional Grammar and Discriminative Estimation Techniques , 2002, ACL.
[27] Rob Malouf,et al. A Comparison of Algorithms for Maximum Entropy Parameter Estimation , 2002, CoNLL.
[28] Ben Taskar,et al. Discriminative Probabilistic Models for Relational Data , 2002, UAI.
[29] Erik F. Tjong Kim Sang,et al. Memory-Based Shallow Parsing , 2002, J. Mach. Learn. Res..
[30] Hanna M. Wallach,et al. Efficient Training of Conditional Random Fields , 2002 .
[31] Michael Collins,et al. New Ranking Algorithms for Parsing and Tagging: Kernels over Discrete Structures, and the Voted Perceptron , 2002, ACL.
[32] Thomas P. Minka,et al. Algorithms for maximum-likelihood logistic regression , 2003 .
[33] Richard M. Schwartz,et al. An Algorithm that Learns What's in a Name , 1999, Machine Learning.