Summarization of legal documents: Where are we now and the way forward
Tài liệu tham khảo
Turtle, 1995, Text retrieval in the legal world, Artif. Intell. Law, 3, 5, 10.1007/BF00877694
Austin, 1975
Bhattacharya, 2019, A comparative study of summarization algorithms applied to legal case judgments, 413
Wikipedia, 2020
Wikipedia, 2020
Press, 2020
Mani, 2001
Farzindar, 2004, Legal text summarization by exploration of the thematic structure and argumentative roles, 27
Kanapala, 2019, Text summarization from legal documents: a survey, Artif. Intell. Rev., 51, 371, 10.1007/s10462-017-9566-2
2020
2020
2020
Michael E. Sykuta, Peter G. Klein, James Cutts, Cori K-Base: Data Overview, in: 2007 Kauffman Symposium on Entrepreneurship and Innovation Data, 2007.
Allahyari, 2017
Gambhir, 2017, Recent automatic text summarization techniques: a survey, Artif. Intell. Rev., 47, 1, 10.1007/s10462-016-9475-9
Nenkova, 2012, A survey of text summarization techniques, 43
Luhn, 1958, The automatic creation of literature abstracts, IBM J. Res. Develop., 2, 159, 10.1147/rd.22.0159
Edmundson, 1969, New methods in automatic extracting, J. ACM, 16, 264, 10.1145/321510.321519
Kai Hong, Ani Nenkova, Improving the estimation of word importance for news multi-document summarization, in: Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, 2014, pp. 712–721.
Nenkova, 2005, 101
Vodolazova, 2013
Vodolazova, 2013, Extractive text summarization: can we use the same techniques for any text?, 164
Aliguliyev, 2009, A new sentence similarity measure and sentence based extractive technique for automatic text summarization, Expert Syst. Appl., 36, 7764, 10.1016/j.eswa.2008.11.022
Li, 2006, Extractive summarization using inter-and intra-event relevance, 369
Maofu Liu, Wenjie Li, Mingli Wu, Qin Lu, Extractive summarization based on event term clustering, in: Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions, 2007, pp. 185–188.
Gabriel Silva, Rafael Ferreira, Rafael Dueire Lins, Luciano Cabral, Hilário Oliveira, Steven J. Simske, Marcelo Riss, Automatic text document summarization based on machine learning, in: Proceedings of the 2015 ACM Symposium on Document Engineering, 2015, pp. 191–194.
Yang, 2017
Fung, 2003, Combining optimal clustering and hidden Markov models for extractive summarization, 21
Celikyilmaz, 2011, Discovery of topically coherent sentences for extractive summarization, 491
Brin, 1998
Mallick, 2019, Graph-based text summarization using modified textrank, 137
Daraksha Parveen, Hans-Martin Ramsl, Michael Strube, Topical coherence for graph-based extractive summarization, in: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015, pp. 1949–1954.
Rada Mihalcea, Paul Tarau, Textrank: Bringing order into text, in: Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, 2004, pp. 404–411.
Erkan, 2004, Lexrank: Graph-based lexical centrality as salience in text summarization, J. Artif. Intell. Res., 22, 457, 10.1613/jair.1523
Gunes Erkan, Dragomir Radev, Lexpagerank: Prestige in multi-document text summarization, in: Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, 2004, pp. 365–371.
Liu, 2019
Pengjie Ren, Zhumin Chen, Zhaochun Ren, Furu Wei, Jun Ma, Maarten de Rijke, Leveraging contextual sentence relations for extractive summarization using a neural attention model, in: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017, pp. 95–104.
Fang, 2017, Word-sentence co-ranking for automatic extractive text summarization, Expert Syst. Appl., 72, 189, 10.1016/j.eswa.2016.12.021
Masaru Isonuma, Toru Fujino, Junichiro Mori, Yutaka Matsuo, Ichiro Sakata, Extractive summarization using multi-task learning with document classification, in: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017, pp. 2101–2110.
Narayan, 2017
Zhang, 2016, Multiview convolutional neural networks for multidocument extractive summarization, IEEE Trans. Cybern., 47, 3230, 10.1109/TCYB.2016.2628402
Nallapati, 2016
R. Vale, R. Lins, R. Ferreira, Assessing sentence simplification methods applied to text summarization, in: 2018 7th Brazilian Conference on Intelligent Systems (BRACIS), 2018, 49–54.
Rafaella Vale, Rafael Dueire Lins, Rafael Ferreira, An assessment of sentence simplification methods in extractive text summarization, in: Proceedings of the ACM Symposium on Document Engineering 2020, 2020, pp. 1–9.
Rush, 2015
Sumit Chopra, Michael Auli, Alexander M Rush, Abstractive sentence summarization with attentive recurrent neural networks, in: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016, pp. 93–98.
Nallapati, 2016
Zhou, 2017
Yan, 2020
Vinyals, 2015, Pointer networks, 2692
See, 2017
Paulus, 2017
Celikyilmaz, 2018
Chen, 2018
Ma, 2018
Tatiana Vodolazova, Elena Lloret, The impact of rule-based text generation on the quality of abstractive summaries, in: Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), 2019, pp. 1275–1284.
Chin-Yew Lin, Rouge: A package for automatic evaluation of summaries ACL, in: Proceedings of Workshop on Text Summarization Branches Out Post Conference Workshop of ACL, 2004, pp. 2017–05.
Claire Grover, Ben Hachey, Ian Hughson, The HOLJ Corpus. Supporting summarisation of legal texts, in: Proceedings of the 5th International Workshop on Linguistically Interpreted Corpora, 2004, pp. 47–54.
Landauer, 1998, An introduction to latent semantic analysis, Discourse Process., 25, 259, 10.1080/01638539809545028
Merchant, 2018, NLP Based latent semantic analysis for legal text summarization, 1803
Jain, 2020, Fine-tuning textrank for legal document summarization: A Bayesian optimization based approach, 41
Hongyan Jing, Sentence reduction for automatic text summarization, in: Sixth Applied Natural Language Processing Conference, 2000, pp. 310–315.
Manor, 2019
Diego Feijo, Viviane Moreira, Summarizing legal rulings: Comparative experiments, in: Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), 2019, pp. 313–322.
Verma, 2017
Galgani, 2015, Summarization based on bi-directional citation analysis, Inform. Process. Manage., 51, 1, 10.1016/j.ipm.2014.08.001
Galgani, 2012, Citation based summarisation of legal texts, 40
Farzindar, 2004, Letsum, an automatic legal text summarizing system, Legal Knowl. Inform. Syst., JURIX, 11
Claire Grover, Ben Hachey, Ian Hughson, Chris Korycinski, Automatic summarisation of legal documents, in: Proceedings of the 9th International Conference on Artificial Intelligence and Law, 2003, pp. 243–251.
Saravanan, 2006, Improving legal document summarization using graphical models, Front. Artif. Intell. Appl., 152, 51
Hachey, 2004, A rhetorical status classifier for legal text summarisation, 35
Teufel, 2002, Summarizing scientific articles: experiments with relevance and rhetorical status, Comput. Linguist., 28, 409, 10.1162/089120102762671936
Bhattacharya, 2019
Pham, 2004, Incremental knowledge acquisition for building sophisticated information extraction systems with kaftie, 292
Galgani, 2012, Combining different summarization techniques for legal text, 115
Duan, 2019, Legal summarization for multi-role debate dialogue via controversy focus mining and multi-task learning, 1361
Kim, 2012, Summarization of legal texts with high cohesion and automatic compression rate, 190
Hachey, 2006, Extractive summarisation of legal texts, Artif. Intell. Law, 14, 305, 10.1007/s10506-007-9039-z
Kanapala, 2019, Summarization of legal judgments using gravitational search algorithm, Neural Comput. Appl., 31, 8631, 10.1007/s00521-019-04177-x
Rashedi, 2009, GSA: a gravitational search algorithm, Inform. Sci., 179, 2232, 10.1016/j.ins.2009.03.004
Le, 2013, Unsupervised keyword extraction for Japanese legal documents, 97
Linwu Zhong, Ziyi Zhong, Zinian Zhao, Siyuan Wang, Kevin D. Ashley, Matthias Grabmair, Automatic summarization of legal decisions using iterative masking of predictive sentences, in: Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law, 2019, pp. 163–172.
Tran, 2018
Anand, 2019, Effective deep learning approaches for summarization of legal texts, J. King Saud Univ.-Comput. Inform. Sci.
Seth Polsley, Pooja Jhunjhunwala, Ruihong Huang, Casesummarizer: a system for automated summarization of legal texts, in: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations, 2016, pp. 258–262.
Galgani, 2010, Lexa: Towards automatic legal citation classification, 445
2020
Syed, 2020
Gohr, 2020
2020
Galgani, 2014, HAUSS: Incrementally building a summarizer combining multiple techniques, Int. J. Hum.-Comput. Stud., 72, 584, 10.1016/j.ijhcs.2014.03.002
Kornilova, 2019
2020
2020
2020
2021
2021
Chieze, 2010, An automatic system for summarization and information extraction of legal information, 216
Kanapala, 2019, Passage-based text summarization for legal information retrieval, Arab. J. Sci. Eng., 44, 9159, 10.1007/s13369-019-03998-1
Mikolov, 2013
Jeffrey Pennington, Richard Socher, Christopher D. Manning, Glove: Global vectors for word representation, in: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP, 2014, pp. 1532–1543.
Chalkidis, 2019, Deep learning in law: early adaptation and legal word embeddings trained on large corpora, Artif. Intell. Law, 27, 171, 10.1007/s10506-018-9238-9