-
2
-
-
0031586003
-
Prediction of complete gene structures in human genomic DNA
-
C. Burge and S. Karlin. Prediction of complete gene structures in human genomic DNA. J. Mol. Biol., 1997.
-
(1997)
J. Mol. Biol.
-
-
Burge, C.1
Karlin, S.2
-
3
-
-
84862292087
-
NP bracketing by maximum entropy tagging and SVMreranking
-
H. Daume and D. Marcu. NP bracketing by maximum entropy tagging and SVMreranking. In Proceedings of EMNLP, 2004.
-
Proceedings of EMNLP, 2004
-
-
Daume, H.1
Marcu, D.2
-
6
-
-
85149144117
-
Adaptive chinese word segmentation
-
J. Gao, A. Wu, M. Li, C. Huang, H. Li, X. Xia, and H. Qin. Adaptive chinese word segmentation. In Proceedings of ACL, 2004.
-
Proceedings of ACL, 2004
-
-
Gao, J.1
Wu, A.2
Li, M.3
Huang, C.4
Li, H.5
Xia, X.6
Qin, H.7
-
8
-
-
0142192295
-
Conditional random fields: Probabilistic models for segmenting and labeling sequence data
-
J. Lafferty, A. McCallum, and F. Pereira. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proceedings of ICML, 2001.
-
Proceedings of ICML, 2001
-
-
Lafferty, J.1
McCallum, A.2
Pereira, F.3
-
9
-
-
77957839409
-
A maximum entropy Chinese character-based parser
-
X. Luo. A maximum entropy Chinese character-based parser. In Proceedings of EMNLP, 2003.
-
Proceedings of EMNLP, 2003
-
-
Luo, X.1
-
11
-
-
77957847281
-
Chinese part-ofspeech tagging: One-at-a-time or all-at-once? Word-based or character-based?
-
H. Ng and J. Low. Chinese part-ofspeech tagging: one-at-a-time or all-at-once? word-based or character-based? In Proceedings of EMNLP, 2004.
-
Proceedings of EMNLP, 2004
-
-
Ng, H.1
Low, J.2
-
12
-
-
85116342676
-
Chinese segmentation and new word detection using conditional random fields
-
F. Peng, F. Feng, and A. McCallum. Chinese segmentation and new word detection using conditional random fields. In Proceedings of COLING, 2004.
-
Proceedings of COLING, 2004
-
-
Peng, F.1
Feng, F.2
McCallum, A.3
-
13
-
-
84982928601
-
Shallow semantic parsing using support vector machines
-
S. Pradhan, W. Ward, K. Hacioglu, J. Martin, and D. Jurafsky. Shallow semantic parsing using support vector machines. In Proceedings of HLT, 2004.
-
Proceedings of HLT, 2004
-
-
Pradhan, S.1
Ward, W.2
Hacioglu, K.3
Martin, J.4
Jurafsky, D.5
-
14
-
-
0025627406
-
The N-best algorithm: An efficient and exact procedure for finding the N most likely sentence hypotheses
-
R. Schwartz and Y. Chow. The N-best algorithm: An efficient and exact procedure for finding the N most likely sentence hypotheses. In Proceedings of ICASSP, 1990.
-
Proceedings of ICASSP, 1990
-
-
Schwartz, R.1
Chow, Y.2
-
19
-
-
14344253846
-
Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data
-
C. Sutton, K. Rohanimanesh, and A. McCallum. Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data. In Proceedings of ICML, 2004.
-
Proceedings of ICML, 2004
-
-
Sutton, C.1
Rohanimanesh, K.2
McCallum, A.3
-
24
-
-
84862272582
-
The integration of syntactic parsing and semantic role labeling
-
S. Yi and M. Palmer. The integration of syntactic parsing and semantic role labeling. In Proceedings of CoNLL, 2005.
-
Proceedings of CoNLL, 2005
-
-
Yi, S.1
Palmer, M.2
|