Summarization of legal documents: Where are we now and the way forward

Computer Science Review - Tập 40 - Trang 100388 - 2021
Deepali Jain1, Malaya Dutta Borah1, Anupam Biswas1
1Department of Computer Science and Engineering, National Institute of Technology Silchar, Assam 788010, India

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