Assisting Authors to Convert Raw Products into Polished Prose

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참고문헌 (59)

1. Agirre, E., "Enriching very large ontologies using the WWW", Procedings of the ECAI 2000 Workshop on Ontology Learning (2000)
2. Andriessen, J., "Computational Psycholinguistics: AI and connectionist models of Human Language processing", pp.247~278 (1996), Taylor and Francis
3. Bateman, J., "Oxford Handbook of Computational Linguistics", pp.284~304 (2003), Oxford University Press
4. Bereiter, C., "The psychology of written composition" (2013), Routledge
5. Bowman, S. R., "A Large Annotated Corpus for Learning Natural Language Inference", Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp.632~642 (2015)
6. Brill, E., "An Improved Error Model for Noisy Channel Spelling Correction", Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics, pp.286~293 (2000)
7. Bryant, C., "Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction", Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pp.793~805 (2017)
8. Cohen, A. D., "Research on direct versus translated writing : Students’ strategies and their results", The Modern Language Journal, 85(2), pp.169~188 (2001)
9. Dale, R., "Helping Our Own: The HOO 2011 Pilot Shared Task", Proceedings of the 13th European Workshop on Natural Language Generation, pp.242~249 (2011)
10. Daudaravičius, V., "Automated Evaluation of Scientific Writing: AESW Shared Task Proposal", Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications, pp.56~63 (2015)
11. De Beaugrande, R., "Text production: Toward a science of composition (Vol. 11)" (1984), Ablex Publishing Corporation
12. Devlin, J., "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding", Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp.4171~4186 (2019)
13. Edunov, S., "Understanding Back-Translation at Scale", Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp.489~500 (2018)
14. Fedus, W., "Maskgan: Better Text Generation via Filling in the", Proceedings of 6th International Conference on Learning Representations (2018)
15. Felice, M., "Automatic Extraction of Learner Errors in ESL Sentences Using Linguistically Enhanced Alignments", Proceedings of the 26th International Conference on Computational Linguistics: Technical Papers, pp.825~835 (2016)
16. Flesch, R., "A new readability yardstick", Journal of Applied Psychology, 32(3), pp.221~233 (1948)
17. Flower, L., "A cognitive process theory of writing", College composition and communication, 32(4), pp.365~387 (1981)
18. François, T., "Recent Advances in Automatic Readability Assessment and Text Simplification (Vol. 165)" (2014), John Benjamins
19. Gatt, A., "Survey of the state of the art in natural language generation : Core tasks, applications and evaluation", Journal of Artificial Intelligence Research, 61, pp.65~170 (2018)
20. Ge, T., "Fluency boost learning and inference for neural grammatical error correction", Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp.1055~1065 (2018)
21. Grangier, D., "QuickEdit : Editing Text & Translations by Crossing Words Out", Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp.272~282 (2018)
22. Halliday, M. A. K., "Cohesion in english" (2014), Routledge
23. Hayes, J. R., "Cognitive Processes in Writing", pp.3~29 (1980), Lawrence Erlbaum Associates
24. Hobbs, J. R., "Coherence and coreference", Cognitive science, 3(1), pp.67~90 (1979)
25. Kellogg, R. T., "The psychology of writing" (1999), Oxford University Press
26. Kessler, J. S., "Scattertext: a Browser-Based Tool for Visualizing how Corpora Differ", Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, System Demonstrations, pp.85~90 (2017)
27. Kingma, D. P., "Adam : A Method for Stochastic Optimization", Proceedings of the 3rd International Conference on Learning Representations (2015)
28. Kiyono, S., "An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction", Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, pp.1236~1242 (2019)
29. Lee, J., "A Corpus of Textual Revisions in Second Language Writing", Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, pp.248~252 (2012)
30. Lichtarge, J., "Corpora Generation for Grammatical Error Correction", Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp.3291~3301 (2019)
31. Logeswaran, L., "Content preserving text generation with attribute controls", Advances in Neural Information Processing Systems, 31, pp.5103~5113 (2018), Curran Associates
32. Mann, W. C., "Natural Language Generation: New Results in Artificial Intelligence, Psychology and Linguistics", pp.85~95 (1987), Springer Netherlands
33. McCoy, K. F., "Natural Language Generation in Artificial Intelligence and Computational Linguistics", pp.103~124 (1991), Kluwer Academic Publishers
34. Meyer, B. J. F., "The organization of prose and its effects on memory (Vol. 1)" (1975), North-Holland
35. Mizumoto, T., "Mining Revision Log of Language Learning SNS for Automated Japanese Error Correction of Second Language Learners", Proceedings of 5th International Joint Conference on Natural Language Processing, pp.147~155 (2011)
36. Napoles, C., "There’s No Comparison: Reference-less Evaluation Metrics in Grammatical Error Correction", Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pp.2109~2115 (2016)
37. Napoles, C., "JFLEG: A Fluency Corpus and Benchmark for Grammatical Error Correction", Proceedings of Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pp.229~234 (2017)
38. Ng, H. T., "The CoNLL-2014 Shared Task on Grammatical Error Correction", Proceedings of the Eighteenth Conference on Computational Natural Language Learning: Shared Task, pp.1~14 (2014)
39. Ott, M., "fairseq: A Fast, Extensible Toolkit for Sequence Modeling", Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations), pp.48~53 (2019)
40. Prabhumoye, S., "Style Transfer Through Back-Translation", Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp.866~876 (2018)
41. Redeker, G., "Abduction, belief and context in dialogue", pp.233~263 (2000), John Benjamins Publishers
42. Reiter, E., "Building Natural Language Generation Systems" (2000), Cambridge University Press
43. Sakaguchi, K., "Reassessing the Goals of Grammatical Error Correction: Fluency instead of Grammaticality", Transactions of the Association for Computational Linguistics, 4(4), pp.169~182 (2016)
44. Sharma, S., "Relevance of Unsupervised Metrics in Task-Oriented Dialogue for Evaluating Natural Language Generation", arXiv preprint arXiv:1706.09799, ~ (2017)
45. Simonin, N., "Advances in Natural Language Generation", pp.146~160 (1988), Pinter Publishers
46. Tan, C., "A Corpus of Sentence-level Revisions in Academic Writing: A Step towards Understanding Statement Strength in Communication", Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, pp.403~408 (2014)
47. Van Dijk, T., "Strategies of discourse comprehension" (1983), New York Academic Press
48. Vaswani, A., "Attention is All you Need", Advances in Neural Information Processing Systems, 31, pp.5998~6008 (2017)
49. Walker, M. A., "Centering theory in discourse" (1998), ClarendonPress
50. Wieting, J., "ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations", Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp.451~462 (2018)
51. Williams, A., "A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference", Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp.1112~1122 (2018)
52. Xie, Z., "Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction", Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp.619~628 (2018)
53. Yuan, Z., "Grammatical Error Correction using Neural Machine Translation", Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp.380~386 (2016)
54. Zhang, F., "A Corpus of Annotated Revisions for Studying Argumentative Writing", Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pp.1568~1578 (2017)
55. Zhang, T., "BERTScore: Evaluating Text Generation with BERT", Proceedings of 8th International Conference on Learning Representations (2020)
56. Zhao, W., "Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data", Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp.156~165 (2019)
57. Zhu, W., "Text Infi lling", arXiv preprint arXiv: 1901.00158, ~ (2019)
58. Zock, Michael, "Cognitive Approach to Natural Language Processing", pp.129~158 (2017), Elsevier
59. Zweig, G., "Computational Approaches to Sentence Completion", Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, pp.601~610 (2012)

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