| Tài liệu tham khảo |
Loại |
Chi tiết |
| [1]. Duglas E.Appelt, D.J.Israel. Introduction to Information Extraction Technology. 1999 |
Sách, tạp chí |
| Tiêu đề: |
Introduction to Information Extraction Technology |
| Tác giả: |
Duglas E. Appelt, D.J. Israel |
| Năm: |
1999 |
|
| [3]. M.Collins. Discriminative Training Methods for Hidden Markov Models: Theory and Experiment with Perceptron Algorithms.2002 |
Sách, tạp chí |
| Tiêu đề: |
Discriminative Training Methods for Hidden Markov Models: Theory and Experiment with Perceptron Algorithms |
| Tác giả: |
M. Collins |
| Năm: |
2002 |
|
| [5]. R.Dugad, U.B.Desai - "A Tutorial on Hidden Markov Model" - Technical Report No: SPANN-96.1, Indian Institute of Technology.1996 |
Sách, tạp chí |
| Tiêu đề: |
A Tutorial on Hidden Markov Model |
|
| [6]. D.Freitag, S.Khadivi. .A Sequence Alignment Model Based on the Averaged Perceptron. 2006 |
Sách, tạp chí |
| Tiêu đề: |
A Sequence Alignment Model Based on the Averaged Perceptron |
| Tác giả: |
D. Freitag, S. Khadivi |
| Năm: |
2006 |
|
| [7]. Freund & Schapire. Large Margin Classification Using the perceptron Algorithm. Machine Learning 37(3) 277-296, 1999 |
Sách, tạp chí |
| Tiêu đề: |
Large Margin Classification Using the perceptron Algorithm |
| Tác giả: |
Freund, Schapire |
| Nhà XB: |
Machine Learning |
| Năm: |
1999 |
|
| [9]. Dong C.Liu and Jorge Nocedal. On the limited memory BFGS method for large scale optimization.Mathematical Programming 45 (1989),pp.503- 528 |
Sách, tạp chí |
| Tiêu đề: |
On the limited memory BFGS method for large scale optimization |
| Tác giả: |
C. Liu Dong, Jorge Nocedal |
| Nhà XB: |
Mathematical Programming |
| Năm: |
1989 |
|
| [11]. A. McCallum, K. Rohanimanesh, and C. Sutton. Dynamic Conditional Random Fields for Jointly Labeling Multiple Sequences. 2004 |
Sách, tạp chí |
| Tiêu đề: |
Dynamic Conditional Random Fields for Jointly Labeling Multiple Sequences |
| Tác giả: |
A. McCallum, K. Rohanimanesh, C. Sutton |
| Năm: |
2004 |
|
| [12]. A.McCallum, C.Shutton. An introduction for Conditional Random Fields for Relational Learning. 2005 |
Sách, tạp chí |
| Tiêu đề: |
An introduction for Conditional Random Fields for Relational Learning |
| Tác giả: |
A. McCallum, C. Shutton |
| Năm: |
2005 |
|
| [14]. A.McCallum, W.li. Early Results for Named Entity Recognition with Conditional Random Fields, Feature Induction and Web-Enhanced Lexicons. 2003 |
Sách, tạp chí |
| Tiêu đề: |
Early Results for Named Entity Recognition with Conditional Random Fields, Feature Induction and Web-Enhanced Lexicons |
| Tác giả: |
A. McCallum, W. Li |
| Năm: |
2003 |
|
| [15]. A.McCallum. Efficiently Inducing Features of Conditional Random Fields. 2003 |
Sách, tạp chí |
| Tiêu đề: |
Efficiently Inducing Features of Conditional Random Fields |
| Tác giả: |
A. McCallum |
| Năm: |
2003 |
|
| [16]. A.B.Poritz - "Hidden Markov Models - A Guide Tour" - IEEE, 1988 |
Sách, tạp chí |
| Tiêu đề: |
Hidden Markov Models - A Guide Tour |
|
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Sách, tạp chí |
| Tiêu đề: |
A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition |
|
| [18]. A.Ratnaparkhi.A maximum entropy model for part-of-speech tagging.In Proc. Emparical Methods for Natural Language Processing, 1996 |
Sách, tạp chí |
| Tiêu đề: |
A maximum entropy model for part-of-speech tagging |
| Tác giả: |
A. Ratnaparkhi |
| Nhà XB: |
Proc. Empirical Methods for Natural Language Processing |
| Năm: |
1996 |
|
| [20]. Sunita Sarawagi, William W. Cohen. Semi-Markov Conditional Random Fields for Information Extraction. 2004 |
Sách, tạp chí |
| Tiêu đề: |
Semi-Markov Conditional Random Fields for Information Extraction |
| Tác giả: |
Sunita Sarawagi, William W. Cohen |
| Năm: |
2004 |
|
| [26]. Tri Tran Q., Thao Pham T.X., Hung Ngo Q., Dien Dinh and Niegl Collier. Named Entitiy Recognition in Vietnamese Document. 2007 |
Sách, tạp chí |
| Tiêu đề: |
Named Entitiy Recognition in Vietnamese Document |
| Tác giả: |
Tri Tran Q., Thao Pham T.X., Hung Ngo Q., Dien Dinh, Niegl Collier |
| Năm: |
2007 |
|
| [2]. A.Berger. The Improved Iterative Scaling Algorithm: A gentle Introdution. School of Computer Science, Carnegie Mellon University. 1999 |
Khác |
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| [8]. J.Lafferty, A.McCallum, and F.Pereira. Conditional random fields: probabilistic models for segmenting and labeling sequence data. In Proc.ICML, 2001 |
Khác |
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| [10]. Walter F.Mascarenhas. The BFGS method with exact line searches fails for non-convex objective functions. Published May 7, 2003 |
Khác |
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| [13]. A.McCallum, D.Freitag, and F. Pereira. Maximum entropy markov models for information extraction and segmentation. In Proc. Iternational Conference on Mechine Learning, 2000, pages 591-598 |
Khác |
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| [19]. B.Roask, M.Saraclar, M.Collins, M.Johnson. Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm.2004 |
Khác |
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