ACL Wiki - User contributions [en]

Semi-supervised Learning in NLP

2009-06-12T14:21:09Z

Pythonner: /* 2007 */

= Semi-supervised Learning for NLP Bibliography =

The goal of this page is to collect all papers focusing on semi-supervised learning for natural language processing. Another good starting point for papers (divided by topic) is John Blitzer and Jerry Zhu's [http://ssl-acl08.wikidot.com/ ACL 2008 tutorial website].

=== 2009 ===

Carlson, A., Betteridge, J., Hruschka Junior, E.R. & Mitchell, T.M. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2201.pdf "Coupling Semi-Supervised Learning of Categories and Relations"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 1-9. Association for Computational Linguistics.

Veeramachaneni, S. & Kondadadi, R.K. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2202.pdf "Surrogate Learning - From Feature Independence to Semi-Supervised Classification"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 10-18. Association for Computational Linguistics.

Goldberg, A.B. & Zhu, X. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2203.pdf "Keepin' It Real: Semi-Supervised Learning with Realistic Tuning"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 19-27. Association for Computational Linguistics.

Zubiaga, A., Fresno, V. & Martínez, R. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2204.pdf "Is Unlabeled Data Suitable for Multiclass SVM-based Web Page Classification?"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 28-36. Association for Computational Linguistics.

Plank, B. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2205.pdf "A Comparison of Structural Correspondence Learning and Self-training for Discriminative Parse Selection"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 37-42. Association for Computational Linguistics.

Andrzejewski, D. & Zhu, X. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2206.pdf "Latent Dirichlet Allocation with Topic-in-Set Knowledge"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 43-48. Association for Computational Linguistics.

Poveda, J., Surdeanu, M. & Turmo, J. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2207.pdf "An Analysis of Bootstrapping for the Recognition of Temporal Expressions"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 49-57. Association for Computational Linguistics.

Liao, W. & Veeramachaneni, S. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2208.pdf "A Simple Semi-supervised Algorithm For Named Entity Recognition"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 58-65. Association for Computational Linguistics.

Chen, Z. & Ji, H. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2209.pdf "Can One Language Bootstrap the Other: A Case Study on Event Extraction"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 66-74. Association for Computational Linguistics.

Huang, J.-T. & Hasegawa-Johnson, M. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2210.pdf "On Semi-Supervised Learning of Gaussian Mixture Models for Phonetic Classification"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 75-83. Association for Computational Linguistics.

Dasgupta, S. & Ng, V. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2211.pdf "Discriminative Models for Semi-Supervised Natural Language Learning"], Invited Position Paper, In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 84-85. Association for Computational Linguistics.

Hal Daume (2009). [http://sites.google.com/site/sslnlp/files/daume09sslnlp.pdf?attredirects=0 "Semi-supervised or Semi-unsupervised?"], Invited Position Paper, In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 84-85. Association for Computational Linguistics.

Fürstenau, H. & Lapata, M. (2009), "Semi-Supervised Semantic Role Labeling", In Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009). Athens, Greece. March 2009., pp. 220-228. Association for Computational Linguistics.

Rao, D. & Ravichandran, D. (2009), "Semi-Supervised Polarity Lexicon Induction", In Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009). Athens, Greece. March 2009., pp. 675-682. Association for Computational Linguistics.

Spoustová, D., Hajič, J., Raab, J. & Spousta, M. (2009), "Semi-Supervised Training for the Averaged Perceptron POS Tagger", In Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009). Athens, Greece. March 2009., pp. 763-771. Association for Computational Linguistics.

Candito, M., Crabbé, B. & Seddah, D. (2009), "On Statistical Parsing of French with Supervised and Semi-Supervised Strategies", In Proceedings of the EACL 2009 Workshop on Computational Linguistic Aspects of Grammatical Inference. Athens, Greece. March 2009., pp. 49-57. Association for Computational Linguistics.

=== 2008 ===
Wang, Q.I., Schuurmans, D. & Lin, D. (2008), "Semi-Supervised Convex Training for Dependency Parsing", In Proceedings of ACL-08: HLT. Columbus, Ohio. June 2008., pp. 532-540. Association for Computational Linguistics.

Koo, T., Carreras, X. & Collins, M. (2008), "Simple Semi-supervised Dependency Parsing", In Proceedings of ACL-08: HLT. Columbus, Ohio. June 2008., pp. 595-603. Association for Computational Linguistics.

Suzuki, J. & Isozaki, H. (2008), "Semi-Supervised Sequential Labeling and Segmentation Using Giga-Word Scale Unlabeled Data", In Proceedings of ACL-08: HLT. Columbus, Ohio. June 2008., pp. 665-673. Association for Computational Linguistics.

Mann, G.S. & McCallum, A. (2008), "Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields", In Proceedings of ACL-08: HLT. Columbus, Ohio. June 2008., pp. 870-878. Association for Computational Linguistics.

Haffari, G. & Sarkar, A. (2008), "Homotopy-Based Semi-Supervised Hidden Markov Models for Sequence Labeling", In Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008). Manchester, UK. August 2008., pp. 305-312.

Wong, K.-F., Wu, M. & Li, W. (2008), "Extractive Summarization Using Supervised and Semi-Supervised Learning", In Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008). Manchester, UK. August 2008., pp. 985-992.

Xu, J., Gao, J., Toutanova, K. & Ney, H. (2008), "Bayesian Semi-Supervised Chinese Word Segmentation for Statistical Machine Translation", In Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008). Manchester, UK. August 2008., pp. 1017-1024.

McClosky, D. & Charniak, E. (2008), "Self-Training for Biomedical Parsing", In Proceedings of ACL-08: HLT, Short Papers. Columbus, Ohio. June 2008., pp. 101-104. Association for Computational Linguistics.

McClosky, D., Charniak, E. & Johnson, M. (2008), "When is Self-Training Effective for Parsing?", In Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008). Manchester, UK. August 2008., pp. 561-568. Coling 2008 Organizing Committee.

=== 2007 ===

Abney, S. (2007), "Semisupervised Learning for Computational Linguistics" Chapman & Hall / CRC.

Chang, M.-W., Ratinov, L. & Roth, D. (2007), "Guiding Semi-Supervision with Constraint-Driven Learning", In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. Prague, Czech Republic. June 2007., pp. 280-287. Association for Computational Linguistics.

Ueffing, N., Haffari, G. & Sarkar, A. (2007), "Transductive learning for statistical machine translation", In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. Prague, Czech Republic. June 2007., pp. 25-32. Association for Computational Linguistics.

Kate, R. & Mooney, R. (2007), "Semi-Supervised Learning for Semantic Parsing using Support Vector Machines", In Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers. Rochester, New York. April 2007., pp. 81-84. Association for Computational Linguistics.

Mann, G. & McCallum, A. (2007), "Efficient Computation of Entropy Gradient for Semi-Supervised Conditional Random Fields", In Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers. Rochester, New York. April 2007., pp. 109-112. Association for Computational Linguistics.

Nadeau, D. (2007), [http://cogprints.org/5859/ "Semi-Supervised Named Entity Recognition: Learning to Recognize 100 Entity Types with Little Supervision"], PhD Thesis, Ottawa, University of Ottawa. December 2007.

Tratz, S. & Sanfilippo, A. (2007), "A High Accuracy Method for Semi-Supervised Information Extraction", In Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers. Rochester, New York. April 2007., pp. 169-172. Association for Computational Linguistics.

Rosenfeld, B. & Feldman, R. (2007), "Using Corpus Statistics on Entities to Improve Semi-supervised Relation Extraction from the Web", In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. Prague, Czech Republic. June 2007., pp. 600-607. Association for Computational Linguistics.

Erkan, G., Ozgur, A. & Radev, D.R. (2007), "Semi-Supervised Classification for Extracting Protein Interaction Sentences using Dependency Parsing", In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). Prague, Czech Republic. June 2007., pp. 228-237. Association for Computational Linguistics.

Suzuki, J., Fujino, A. & Isozaki, H. (2007), "Semi-Supervised Structured Output Learning Based on a Hybrid Generative and Discriminative Approach", In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). Prague, Czech Republic. June 2007., pp. 791-800. Association for Computational Linguistics.

=== 2006 ===

Duh, K. & Kirchhoff, K. (2006), "Lexicon Acquisition for Dialectal Arabic Using Transductive Learning", In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing. Sydney, Australia. July 2006., pp. 399-407. Association for Computational Linguistics.

Chen, J., Ji, D., Tan, C.L. & Niu, Z. (2006), "Relation Extraction Using Label Propagation Based Semi-Supervised Learning", In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics. Sydney, Australia. July 2006., pp. 129-136. Association for Computational Linguistics.

Jiao, F., Wang, S., Lee, C.-H., Greiner, R. & Schuurmans, D. (2006), "Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling", In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics. Sydney, Australia. July 2006., pp. 209-216. Association for Computational Linguistics.

Frunza, O. & Inkpen, D. (2006), "Semi-Supervised Learning of Partial Cognates Using Bilingual Bootstrapping", In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics. Sydney, Australia. July 2006., pp. 441-448. Association for Computational Linguistics.

Fraser, A. & Marcu, D. (2006), "Semi-Supervised Training for Statistical Word Alignment", In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics. Sydney, Australia. July 2006., pp. 769-776. Association for Computational Linguistics.

Levow, G.-A. (2006), "Unsupervised and Semi-supervised Learning of Tone and Pitch Accent", In Proceedings of the Human Language Technology Conference of the NAACL, Main Conference. New York City, USA. June 2006., pp. 224-231. Association for Computational Linguistics.

=== 2005 ===

Mohit, B. & Hwa, R. (2005), "Syntax-based Semi-Supervised Named Entity Tagging", In Proceedings of the ACL Interactive Poster and Demonstration Sessions. Ann Arbor, Michigan. June 2005., pp. 57-60. Association for Computational Linguistics.

Niu, Z.-Y., Ji, D.-H. & Tan, C.L. (2005), "Word Sense Disambiguation Using Label Propagation Based Semi-Supervised Learning", In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL'05). Ann Arbor, Michigan. June 2005., pp. 395-402. Association for Computational Linguistics.

=== 2004 ===

Claveau, V. & Sébillot, P. (2004), "From efficiency to portability: acquisition of semantic relations by semi-supervised machine learning ", In Proceedings of Coling 2004 . Geneva, Switzerland. Aug 23--Aug 27 2004., pp. 261-267. COLING.

Schulz, S., Markó, K., Sbrissia, E., Nohama, P. & Hahn, U. (2004), "Cognate Mapping - A Heuristic Strategy for the Semi-Supervised Acquisition of a Spanish Lexicon from a Portuguese Seed Lexicon ", In Proceedings of Coling 2004 . Geneva, Switzerland. Aug 23--Aug 27 2004., pp. 813-819. COLING.

Su, W., Carpuat, M. & Wu, D. (2004), "Semi-supervised training of a Kernel PCA-Based Model for Word Sense Disambiguation ", In Proceedings of Coling 2004 . Geneva, Switzerland. Aug 23--Aug 27 2004., pp. 1298-1304. COLING.

Semi-supervised Learning in NLP

2009-06-12T14:19:58Z

Pythonner: /* 2007 */

= Semi-supervised Learning for NLP Bibliography =

The goal of this page is to collect all papers focusing on semi-supervised learning for natural language processing. Another good starting point for papers (divided by topic) is John Blitzer and Jerry Zhu's [http://ssl-acl08.wikidot.com/ ACL 2008 tutorial website].

=== 2009 ===

Carlson, A., Betteridge, J., Hruschka Junior, E.R. & Mitchell, T.M. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2201.pdf "Coupling Semi-Supervised Learning of Categories and Relations"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 1-9. Association for Computational Linguistics.

Veeramachaneni, S. & Kondadadi, R.K. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2202.pdf "Surrogate Learning - From Feature Independence to Semi-Supervised Classification"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 10-18. Association for Computational Linguistics.

Goldberg, A.B. & Zhu, X. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2203.pdf "Keepin' It Real: Semi-Supervised Learning with Realistic Tuning"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 19-27. Association for Computational Linguistics.

Zubiaga, A., Fresno, V. & Martínez, R. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2204.pdf "Is Unlabeled Data Suitable for Multiclass SVM-based Web Page Classification?"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 28-36. Association for Computational Linguistics.

Plank, B. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2205.pdf "A Comparison of Structural Correspondence Learning and Self-training for Discriminative Parse Selection"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 37-42. Association for Computational Linguistics.

Andrzejewski, D. & Zhu, X. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2206.pdf "Latent Dirichlet Allocation with Topic-in-Set Knowledge"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 43-48. Association for Computational Linguistics.

Poveda, J., Surdeanu, M. & Turmo, J. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2207.pdf "An Analysis of Bootstrapping for the Recognition of Temporal Expressions"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 49-57. Association for Computational Linguistics.

Liao, W. & Veeramachaneni, S. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2208.pdf "A Simple Semi-supervised Algorithm For Named Entity Recognition"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 58-65. Association for Computational Linguistics.

Chen, Z. & Ji, H. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2209.pdf "Can One Language Bootstrap the Other: A Case Study on Event Extraction"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 66-74. Association for Computational Linguistics.

Huang, J.-T. & Hasegawa-Johnson, M. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2210.pdf "On Semi-Supervised Learning of Gaussian Mixture Models for Phonetic Classification"], In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 75-83. Association for Computational Linguistics.

Dasgupta, S. & Ng, V. (2009), [http://www.aclweb.org/anthology/W/W09/W09-2211.pdf "Discriminative Models for Semi-Supervised Natural Language Learning"], Invited Position Paper, In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 84-85. Association for Computational Linguistics.

Hal Daume (2009). [http://sites.google.com/site/sslnlp/files/daume09sslnlp.pdf?attredirects=0 "Semi-supervised or Semi-unsupervised?"], Invited Position Paper, In Proceedings of the NAACL HLT Workshop on Semi-supervised Learning for Natural Language Processing. Boulder, Colorado, USA. June 2009., pp. 84-85. Association for Computational Linguistics.

Fürstenau, H. & Lapata, M. (2009), "Semi-Supervised Semantic Role Labeling", In Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009). Athens, Greece. March 2009., pp. 220-228. Association for Computational Linguistics.

Rao, D. & Ravichandran, D. (2009), "Semi-Supervised Polarity Lexicon Induction", In Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009). Athens, Greece. March 2009., pp. 675-682. Association for Computational Linguistics.

Spoustová, D., Hajič, J., Raab, J. & Spousta, M. (2009), "Semi-Supervised Training for the Averaged Perceptron POS Tagger", In Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009). Athens, Greece. March 2009., pp. 763-771. Association for Computational Linguistics.

Candito, M., Crabbé, B. & Seddah, D. (2009), "On Statistical Parsing of French with Supervised and Semi-Supervised Strategies", In Proceedings of the EACL 2009 Workshop on Computational Linguistic Aspects of Grammatical Inference. Athens, Greece. March 2009., pp. 49-57. Association for Computational Linguistics.

=== 2008 ===
Wang, Q.I., Schuurmans, D. & Lin, D. (2008), "Semi-Supervised Convex Training for Dependency Parsing", In Proceedings of ACL-08: HLT. Columbus, Ohio. June 2008., pp. 532-540. Association for Computational Linguistics.

Koo, T., Carreras, X. & Collins, M. (2008), "Simple Semi-supervised Dependency Parsing", In Proceedings of ACL-08: HLT. Columbus, Ohio. June 2008., pp. 595-603. Association for Computational Linguistics.

Suzuki, J. & Isozaki, H. (2008), "Semi-Supervised Sequential Labeling and Segmentation Using Giga-Word Scale Unlabeled Data", In Proceedings of ACL-08: HLT. Columbus, Ohio. June 2008., pp. 665-673. Association for Computational Linguistics.

Mann, G.S. & McCallum, A. (2008), "Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields", In Proceedings of ACL-08: HLT. Columbus, Ohio. June 2008., pp. 870-878. Association for Computational Linguistics.

Haffari, G. & Sarkar, A. (2008), "Homotopy-Based Semi-Supervised Hidden Markov Models for Sequence Labeling", In Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008). Manchester, UK. August 2008., pp. 305-312.

Wong, K.-F., Wu, M. & Li, W. (2008), "Extractive Summarization Using Supervised and Semi-Supervised Learning", In Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008). Manchester, UK. August 2008., pp. 985-992.

Xu, J., Gao, J., Toutanova, K. & Ney, H. (2008), "Bayesian Semi-Supervised Chinese Word Segmentation for Statistical Machine Translation", In Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008). Manchester, UK. August 2008., pp. 1017-1024.

McClosky, D. & Charniak, E. (2008), "Self-Training for Biomedical Parsing", In Proceedings of ACL-08: HLT, Short Papers. Columbus, Ohio. June 2008., pp. 101-104. Association for Computational Linguistics.

McClosky, D., Charniak, E. & Johnson, M. (2008), "When is Self-Training Effective for Parsing?", In Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008). Manchester, UK. August 2008., pp. 561-568. Coling 2008 Organizing Committee.

=== 2007 ===

Abney, S. (2007), "Semisupervised Learning for Computational Linguistics" Chapman & Hall / CRC.

Chang, M.-W., Ratinov, L. & Roth, D. (2007), "Guiding Semi-Supervision with Constraint-Driven Learning", In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. Prague, Czech Republic. June 2007., pp. 280-287. Association for Computational Linguistics.

Ueffing, N., Haffari, G. & Sarkar, A. (2007), "Transductive learning for statistical machine translation", In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. Prague, Czech Republic. June 2007., pp. 25-32. Association for Computational Linguistics.

Kate, R. & Mooney, R. (2007), "Semi-Supervised Learning for Semantic Parsing using Support Vector Machines", In Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers. Rochester, New York. April 2007., pp. 81-84. Association for Computational Linguistics.

Mann, G. & McCallum, A. (2007), "Efficient Computation of Entropy Gradient for Semi-Supervised Conditional Random Fields", In Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers. Rochester, New York. April 2007., pp. 109-112. Association for Computational Linguistics.

Nadeau, D. (2007), "Semi-Supervised Named Entity Recognition: Learning to Recognize 100 Entity Types with Little Supervision", PhD Thesis, Ottawa, University of Ottawa. December 2007.

Tratz, S. & Sanfilippo, A. (2007), "A High Accuracy Method for Semi-Supervised Information Extraction", In Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers. Rochester, New York. April 2007., pp. 169-172. Association for Computational Linguistics.

Rosenfeld, B. & Feldman, R. (2007), "Using Corpus Statistics on Entities to Improve Semi-supervised Relation Extraction from the Web", In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. Prague, Czech Republic. June 2007., pp. 600-607. Association for Computational Linguistics.

Erkan, G., Ozgur, A. & Radev, D.R. (2007), "Semi-Supervised Classification for Extracting Protein Interaction Sentences using Dependency Parsing", In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). Prague, Czech Republic. June 2007., pp. 228-237. Association for Computational Linguistics.

Suzuki, J., Fujino, A. & Isozaki, H. (2007), "Semi-Supervised Structured Output Learning Based on a Hybrid Generative and Discriminative Approach", In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). Prague, Czech Republic. June 2007., pp. 791-800. Association for Computational Linguistics.

=== 2006 ===

Duh, K. & Kirchhoff, K. (2006), "Lexicon Acquisition for Dialectal Arabic Using Transductive Learning", In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing. Sydney, Australia. July 2006., pp. 399-407. Association for Computational Linguistics.

Chen, J., Ji, D., Tan, C.L. & Niu, Z. (2006), "Relation Extraction Using Label Propagation Based Semi-Supervised Learning", In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics. Sydney, Australia. July 2006., pp. 129-136. Association for Computational Linguistics.

Jiao, F., Wang, S., Lee, C.-H., Greiner, R. & Schuurmans, D. (2006), "Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling", In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics. Sydney, Australia. July 2006., pp. 209-216. Association for Computational Linguistics.

Frunza, O. & Inkpen, D. (2006), "Semi-Supervised Learning of Partial Cognates Using Bilingual Bootstrapping", In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics. Sydney, Australia. July 2006., pp. 441-448. Association for Computational Linguistics.

Fraser, A. & Marcu, D. (2006), "Semi-Supervised Training for Statistical Word Alignment", In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics. Sydney, Australia. July 2006., pp. 769-776. Association for Computational Linguistics.

Levow, G.-A. (2006), "Unsupervised and Semi-supervised Learning of Tone and Pitch Accent", In Proceedings of the Human Language Technology Conference of the NAACL, Main Conference. New York City, USA. June 2006., pp. 224-231. Association for Computational Linguistics.

=== 2005 ===

Mohit, B. & Hwa, R. (2005), "Syntax-based Semi-Supervised Named Entity Tagging", In Proceedings of the ACL Interactive Poster and Demonstration Sessions. Ann Arbor, Michigan. June 2005., pp. 57-60. Association for Computational Linguistics.

Niu, Z.-Y., Ji, D.-H. & Tan, C.L. (2005), "Word Sense Disambiguation Using Label Propagation Based Semi-Supervised Learning", In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL'05). Ann Arbor, Michigan. June 2005., pp. 395-402. Association for Computational Linguistics.

=== 2004 ===

Claveau, V. & Sébillot, P. (2004), "From efficiency to portability: acquisition of semantic relations by semi-supervised machine learning ", In Proceedings of Coling 2004 . Geneva, Switzerland. Aug 23--Aug 27 2004., pp. 261-267. COLING.

Schulz, S., Markó, K., Sbrissia, E., Nohama, P. & Hahn, U. (2004), "Cognate Mapping - A Heuristic Strategy for the Semi-Supervised Acquisition of a Spanish Lexicon from a Portuguese Seed Lexicon ", In Proceedings of Coling 2004 . Geneva, Switzerland. Aug 23--Aug 27 2004., pp. 813-819. COLING.

Su, W., Carpuat, M. & Wu, D. (2004), "Semi-supervised training of a Kernel PCA-Based Model for Word Sense Disambiguation ", In Proceedings of Coling 2004 . Geneva, Switzerland. Aug 23--Aug 27 2004., pp. 1298-1304. COLING.

CONLL-2003 (State of the art)

2007-08-07T15:08:13Z

Pythonner:

* '''Performance measure:''' F = 2 * Precision * Recall / (Recall + Precision)
* '''Precision:''' percentage of named entities found by the algorithm that are correct
* '''Recall:''' percentage of named entities defined in the corpus that were found by the program
* Exact match (for all words of a chunk) is used in the calculation of precision and recall (see [http://www.cnts.ua.ac.be/conll2000/chunking/output.html CONLL scoring software])

* '''Training data:''' Train split of CONLL-2003 corpus
* '''Dryrun data:''' Testa split of CONLL-2003 corpus
* '''Testing data:''' Testb split of CONLL-2003 corpus
* The corpus contains a very high ratio of metonymic references (city names standing for sport teams)

== Table of results ==

{| border="1" cellpadding="5" cellspacing="1" width="100%"
|-
! System name
! Short description
! System type (1)
! Main publications
! Software
! Results
|-
| FIJZ
| Best CONLL-2003 participant
| S
| Florian, Ittycheriah, Jing and Zhang (2003)
| -
| 88.76%
|-
| Baseline
| Vocabulary transfer from training to testing
| S
| Tjong Kim Sang and De Meulder(2003)
| -
| 59.61%
|-
| Balie
| Unsupervised approach: no prior training
| U
| Nadeau, Turney and Matwin (2006)
| [http://balie.sourceforge.net sourceforge.net]
| 55.98%
|-
|}

* (1) '''System type''': R = hand-crafted rules, S = supervised learning, U = unsupervised learning, H = hybrid

== References ==

Florian, R., Ittycheriah, A., Jing, H. and Zhang, T. (2003) [http://www.cnts.ua.ac.be/conll2003/pdf/16871flo.pdf Named Entity Recognition through Classifier Combination]. ''Proceedings of CoNLL-2003''. Edmonton, Canada.

Nadeau, D., Turney, P. D. and Matwin, S. (2006) [http://iit-iti.nrc-cnrc.gc.ca/publications/nrc-48727_e.html Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity]. ''Proceedings 19th Canadian Conference on Artificial Intelligence''. Québec, Canada.

Tjong Kim Sang, E. F. and De Meulder, F. (2003) [http://www.cnts.ua.ac.be/conll2003/pdf/14247tjo.pdf Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition]. ''Proceedings of CoNLL-2003''. Edmonton, Canada.

== See also ==

* [[Named Entity Recognition (State of the art)|Named Entity Recognition]]
* [[State of the art]]

[[Category:State of the art]]

MUC-7 (State of the art)

2007-08-07T13:51:41Z

Pythonner:

* '''Performance measure:''' F = 2 * Precision * Recall / (Recall + Precision)
* '''Precision:''' percentage of named entities found by the algorithm that are correct
* '''Recall:''' percentage of named entities defined in the corpus that were found by the program
* Exact calculation of precision and recall is explained in the [http://www.itl.nist.gov/iad/894.02/related_projects/muc/muc_sw/muc_sw_manual.html MUC scoring software]

* '''Training data:''' Training section of MUC-7 dataset
* '''Dryrun data:''' Dryrun section of MUC-7 dataset
* '''Testing data:''' Formal section of MUC-7 dataset

== Table of results ==

{| border="1" cellpadding="5" cellspacing="1" width="100%"
|-
! System name
! Short description
! System type (1)
! Main publications
! Software
! Results
|-
| Annotator
| Human annotator
| -
| [http://www.itl.nist.gov/iad/894.02/related_projects/muc/proceedings/muc_7_toc.html MUC-7 proceedings]
| -
| 97.60%
|-
| LTG
| Best MUC-7 participant
| H
| Mikheev, Grover and Moens (1998)
| -
| 93.39%
|-
| Balie
| Unsupervised approach: no prior training
| U
| Nadeau, Turney and Matwin (2006)
| [http://balie.sourceforge.net sourceforge.net]
| 77.71% (2)
|-
| Baseline
| Vocabulary transfer from training to testing
| S
| Whitelaw and Patrick (2003)
| -
| 58.89% (2)
|-
|}

* (1) '''System type''': R = hand-crafted rules, S = supervised learning, U = unsupervised learning, H = hybrid
* (2) Calculated on Enamex types only.

== References ==

Mikheev, A., Grover, C. and Moens, M. (1998). [http://www-nlpir.nist.gov/related_projects/muc/proceedings/muc_7_proceedings/ltg_muc7.pdf Description of the LTG system used for MUC-7]. ''Proceedings of the Seventh Message Understanding Conference (MUC-7)''. Fairfax, Virginia.

Nadeau, D., Turney, P. D. and Matwin, S. (2006) [http://iit-iti.nrc-cnrc.gc.ca/publications/nrc-48727_e.html Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity]. ''Proceedings 19th Canadian Conference on Artificial Intelligence''. Québec, Canada.

Whitelaw, C. and Patrick, J. (2003) [http://www.springerlink.com/content/ju66c6a2734fl20u/ Evaluating Corpora for Named Entity Recognition Using Character-Level Features]. ''Proceeding of the 16th Australian Conference on AI''. Perth, Australia.

== See also ==

* [[Named Entity Recognition (State of the art)|Named Entity Recognition]]
* [[State of the art]]

[[Category:State of the art]]

Named Entity Recognition (State of the art)

2007-08-07T13:29:21Z

Pythonner:

== MUC-6 Evaluation ==
* stub

== MUC-7 Evaluation ==

* In MUC-7, named entities were defined as proper names and quantities of interest. Person, organization, and location names were marked as well as dates, times, percentages, and monetary amounts.
* MUC-7 [http://www.itl.nist.gov/iad/894.02/related_projects/muc/proceedings/muc_7_toc.html proceedings]
* State-of-the-art results for [[MUC-7 (State of the art)|MUC-7]]

== CONLL-2002 Evaluation ==
* stub

== CONLL-2003 Evaluation ==
* CONLL-2003 concentrates on four types of named entities: persons, locations, organizations and names of miscellaneous entities that do not belong to the previous three groups.
* CONLL-2003 [http://www.cnts.ua.ac.be/conll2003/proceedings.html proceedings]
* State-of-the-art results for [[CONLL-2003 (State of the art)|CONLL-2003]]

[[Category:State of the art]]

MUC-7 (State of the art)

2007-07-31T19:59:46Z

Pythonner:

* '''Performance measure:''' F = 2 * Precision * Recall / (Recall + Precision)
* '''Precision:''' percentage of named entities found by the algorithm that are correct
* '''Recall:''' percentage of named entities defined in the corpus that were found by the program
* Exact calculation of precision and recall is explained in the [http://www.itl.nist.gov/iad/894.02/related_projects/muc/muc_sw/muc_sw_manual.html MUC scoring software]

* '''Training data:''' Training section of MUC-7 dataset
* '''Testing data:''' Formal section of MUC-7 dataset

== Table of results ==

{| border="1" cellpadding="5" cellspacing="1" width="100%"
|-
! System name
! Short description
! System type (1)
! Main publications
! Software
! Results
|-
| Annotator
| Human annotator
| -
| [http://www.itl.nist.gov/iad/894.02/related_projects/muc/proceedings/muc_7_toc.html MUC-7 proceedings]
| -
| 97.60%
|-
| LTG
| Best MUC-7 participant
| H
| Mikheev, Grover and Moens (1998)
| -
| 93.39%
|-
| Balie
| Unsupervised approach: no prior training
| U
| Nadeau, Turney and Matwin (2006)
| [http://balie.sourceforge.net sourceforge.net]
| 77.71% (2)
|-
| Baseline
| Vocabulary transfer from training to testing
| S
| Whitelaw and Patrick (2003)
| -
| 58.89% (2)
|-
|}

* (1) '''System type''': R = hand-crafted rules, S = supervised learning, U = unsupervised learning, H = hybrid
* (2) Calculated on Enamex types only.

== References ==

Mikheev, A., Grover, C. and Moens, M. (1998). [http://www-nlpir.nist.gov/related_projects/muc/proceedings/muc_7_proceedings/ltg_muc7.pdf Description of the LTG system used for MUC-7]. ''Proceedings of the Seventh Message Understanding Conference (MUC-7)''. Fairfax, Virginia.

Nadeau, D., Turney, P. D. and Matwin, S. (2006) [http://iit-iti.nrc-cnrc.gc.ca/publications/nrc-48727_e.html Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity]. ''Proceedings 19th Canadian Conference on Artificial Intelligence''. Québec, Canada.

Whitelaw, C. and Patrick, J. (2003) [http://www.springerlink.com/content/ju66c6a2734fl20u/ Evaluating Corpora for Named Entity Recognition Using Character-Level Features]. ''Proceeding of the 16th Australian Conference on AI''. Perth, Australia.

== See also ==

* [[Named Entity Recognition (State of the art)|Named Entity Recognition]]
* [[State of the art]]

[[Category:State of the art]]

Named Entity Recognition (State of the art)

2007-07-31T19:58:51Z

Pythonner:

MUC-7 (State of the art)

2007-07-31T19:53:21Z

Pythonner:

* '''Performance measure:''' F = 2 * Precision * Recall / (Recall + Precision)
* '''Precision:''' percentage of named entities found by the algorithm that are correct
* '''Recall:''' percentage of named entities defined in the corpus that were found by the program
* Exact calculation of precision and recall is explained in the [http://www.itl.nist.gov/iad/894.02/related_projects/muc/muc_sw/muc_sw_manual.html MUC scoring software]

* '''Training data:''' Training section of MUC-7 dataset
* '''Testing data:''' Formal section of MUC-7 dataset

== Table of results ==

{| border="1" cellpadding="5" cellspacing="1" width="100%"
|-
! System name
! Short description
! System type (1)
! Main publications
! Software
! Results
|-
| Annotator
| Human annotator
| -
| [http://www.itl.nist.gov/iad/894.02/related_projects/muc/proceedings/muc_7_toc.html MUC-7 proceedings]
| -
| 97.60%
|-
| LTG
| Best MUC-7 participant
| H
| Mikheev, Grover and Moens (1998)
| -
| 93.39%
|-
| Balie
| Unsupervised approach: no prior training
| U
| Nadeau, Turney and Matwin (2006)
| [http://balie.sourceforge.net sourceforge.net]
| 77.71% (2)
|-
| Baseline
| Vocabulary transfer from training to testing
| S
| Whitelaw and Patrick (2003)
| -
| 58.89% (2)
|-
|}

* (1) '''System type''': R = hand-crafted rules, S = supervised learning, U = unsupervised learning, H = hybrid
* (2) Calculated on Enamex types only.

== References ==

Mikheev, A., Grover, C. and Moens, M. (1998). [http://www-nlpir.nist.gov/related_projects/muc/proceedings/muc_7_proceedings/ltg_muc7.pdf Description of the LTG system used for MUC-7]. ''Proceedings of the Seventh Message Understanding Conference (MUC-7)''. Fairfax, Virginia.

Nadeau, D., Turney, P. D. and Matwin, S. (2006) [http://iit-iti.nrc-cnrc.gc.ca/publications/nrc-48727_e.html Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity]. ''Proceedings 19th Canadian Conference on Artificial Intelligence''. Québec, Canada.

Whitelaw, C. and Patrick, J. (2003) [http://www.springerlink.com/content/ju66c6a2734fl20u/ Evaluating Corpora for Named Entity Recognition Using Character-Level Features]. ''Proceeding of the 16th Australian Conference on AI''. Perth, Australia.

== See also ==

* [[Named Entity Recognition (State of the art)|Named Entity Recognition]]
* [[State of the art]]

MUC-7 (State of the art)

2007-07-31T19:35:20Z

Pythonner:

* '''Performance measure:''' F = 2 * Precision * Recall / (Recall + Precision)
* '''Precision:''' percentage of named entities found by the algorithm that are correct
* '''Recall:''' percentage of named entities defined in the corpus that were found by the program
* Exact calculation of precision and recall is explained in the [http://www.itl.nist.gov/iad/894.02/related_projects/muc/muc_sw/muc_sw_manual.html MUC scoring software]

* '''Training data:''' Training section of MUC-7 dataset
* '''Testing data:''' Formal section of MUC-7 dataset

== Table of results ==

{| border="1" cellpadding="5" cellspacing="1" width="100%"
|-
! System name
! Short description
! System type
! Main publications
! Software
! Results (F)
|-
| Annotator
| Human annotator
| -
| [http://www.itl.nist.gov/iad/894.02/related_projects/muc/proceedings/muc_7_toc.html MUC-7 proceedings]
| -
| 97.60%
|-
| LTG
| Best MUC-7 participant
| H
| Mikheev, Grover and Moens (1998)
| -
| 93.39%
|-
| Baseline
| Vocabulary transfer from training to testing
| S
| Whitelaw and Patrick (2003)
| -
| 58.89%
|-
|}

* '''System type''': R = hand-crafted rules, S = supervised learning, U = unsupervised learning, H = hybrid

== References ==

Mikheev, A., Grover, C. and Moens, M. (1998). [http://www-nlpir.nist.gov/related_projects/muc/proceedings/muc_7_proceedings/ltg_muc7.pdf Description of the LTG system used for MUC-7]. ''Proceedings of the Seventh Message Understanding Conference (MUC-7)''. Fairfax, Virginia.

Whitelaw, C. and Patrick, J. (2003) [http://www.springerlink.com/content/ju66c6a2734fl20u/ Evaluating Corpora for Named Entity Recognition Using Character-Level Features]. ''Proceeding of the 16th Australian Conference on AI''. Perth, Australia.

== See also ==

* [[Named Entity Recognition (State of the art)|Named Entity Recognition]]
* [[State of the art]]

MUC-7 (State of the art)

2007-07-31T19:01:44Z

Pythonner:

State of the art

2007-07-31T19:00:27Z

Pythonner:

The purpose of this section of the ACL wiki is to be a repository of ''k''-best state-of-the-art results (i.e., methods and software) for various core natural language processing tasks.

As a side effect, this should hopefully evolve into a knowledge base of standard evaluation methods and datasets for various tasks, as well as encourage more effort into reproducibility of results. This will help newcomers to a field appreciate what has been done so far and what the main tasks are, and will help keep active researchers informed on fields other than their specific research. The next time you need a system for PP attachment, or wonder what is the current state of word sense disambiguation, this will be the place to visit.

Please contribute! (This is also a good place for you to display your results!)


* [[Anaphora Resolution (State of the art)|Anaphora Resolution]] (stub)
* [[Attributional and Relational Similarity (State of the art)|Attributional and Relational Similarity]]
* [[Chunking (State of the art)|Chunking]] (stub)
* [[Dependency Parsing (State of the art)|Dependency Parsing]] (stub)
* [[Document Classification (State of the art)|Document Classification]] (stub)
* [[Named Entity Recognition (State of the art)|Named Entity Recognition]]
* [[NP Chunking (State of the art)|NP Chunking]]
* [[Parsing (State of the art)|Parsing]]
* [[POS Tagging (State of the art) |POS Tagging]]
* [[PP Attachment (State of the art)|PP Attachment]] (stub)
* [[Semantic Role Labeling (State of the art)|Semantic Role Labeling]] (stub)
* [[Sentiment Analysis (State of the art)|Sentiment Analysis]] (stub)
* [[Word Sense Disambiguation (State of the art)|Word Sense Disambiguation]] (stub)


[[Category:State of the art]]

MUC-7 (State of the art)

2007-07-31T18:58:41Z

Pythonner:

MUC-7 (State of the art)

2007-07-31T18:57:42Z

Pythonner:

Named Entity Recognition (State of the art)

2007-07-31T18:32:46Z

Pythonner:

== MUC-6 Evaluation ==

== MUC-7 Evaluation ==

* In MUC-7, named entities were defined as proper names and quantities of interest. Person, organization, and location names were marked as well as dates, times, percentages, and monetary amounts.
* MUC-7 [http://www.itl.nist.gov/iad/894.02/related_projects/muc/proceedings/muc_7_toc.html proceedings]
* State-of-the-art results for [[MUC-7 (State of the art)|MUC-7]]

== CONLL-2002 Evaluation ==

== CONLL-2003 Evaluation ==

[[Category:State of the art]]

Named entity recognizers

2007-05-01T19:14:42Z

Pythonner:

'''[[Software]] - Named entity recognizers'''


* [http://www.aueb.gr/users/ion/software/GREEK_NERC_v2.tar.gz Greek named entity recognizer (version 2)] - currently identifies temporal expressions, person names, and organization names; see [http://www.aueb.gr/users/ion/publications.html here] for publications describing the recognizer
* [http://l2r.cs.uiuc.edu/~cogcomp/asoftware.php?skey=NE English named entity recognizer] - identifies/classifies entities as Person, Location, Organization and Misc (this last category relates to languages and nationalities); fast and robust; try the [http://l2r.cs.uiuc.edu/~cogcomp/ne_demo.php demo]
*[http://balie.sourceforge.net/ Balie] Baseline implementation of named entity recognition.

[[Category:Software]]