Open Access
Issue
E3S Web of Conf.
Volume 529, 2024
International Conference on Sustainable Goals in Materials, Energy and Environment (ICSMEE’24)
Article Number 04019
Number of page(s) 15
Section Advanced Interdisciplinary Approaches
DOI https://doi.org/10.1051/e3sconf/202452904019
Published online 29 May 2024
  1. Annamalai Narayanan; Mahinthan Chandramohan; Rajasekar Venkatesan; Lihui Chen; Yang Liu; Shantanu Jaiswal graph2vec: Learning Distributed Representations of Graphs In arXiv:1707.05005v1 [cs.AI](2017). [Google Scholar]
  2. Bhattacharya P; Hiware K; Rajgaria S; Pochhi N; Ghosh K; Ghosh SA comparative study of summarization algorithms applied to legal case judgments. In: European conference on information retrieval, Springer, pp 413–428(2019a). [Google Scholar]
  3. Chalkidis I; Kampas D Deep learning in law: early adaptation and legal word embeddings trained on large corpora. Artificial Intell Law 27(2):171–198(2019). [Google Scholar]
  4. Chalkidis I; Fergadiotis M; Malakasiotis P; Aletras N; Androutsopoulos I LEGAL-BERT: the muppets straight out of law school. In: fndings of the association for computational Linguistics: EMNLP 2020, pp 2898–2904, https://huggingface.co/nlpaueb/legal-bert-base-uncased(2020). [Google Scholar]
  5. Devlin J; Chang MW; Lee K; Toutanova K Bert: Pre-training of deep bidirectional transformers for language understanding. In: proceedings of NAACL-HLT 2019 pp. 4171–4186, https://huggingface.co/bert-base-uncased(2019). [Google Scholar]
  6. Farhangi ALegal domain-specific pre-trained word vectors. https://github.com/ashkonf/LeGloVe(2018). [Google Scholar]
  7. Farzindar A; Lapalme G Letsum, an automatic legal text summarizing system. In: legal knowledge and information systems–JURIX, pp. 11–18(2004). [Google Scholar]
  8. Graves A; Fernández S; Schmidhuber J Bidirectional LSTM networks for improved phoneme classifcation and recognition. In: proceedings of the international conference on artifcial neural networks (ICANN), pp. 799–804(2005). [Google Scholar]
  9. Hachey B, Grover C Extractive summarisation of legal texts. Artif Intell Law 14(4):305–345(2006). [Google Scholar]
  10. H. Cunningham; D. Maynard; K. Bontcheva; V. Tablan, “GATE: A Framework and Graphical De velopment Environment for Robust NLP Tools and Applications,” in Proc. ACL(2002). [Google Scholar]
  11. Jenish Dhanani; Rupa Mehta; Dipti Ranal Effective and scalable legal judgment recommendation using pre-learned word embedding In Complex & Intelligent Systems (2022) 8:3199–3213(2022). [Google Scholar]
  12. Joseph L Fleiss; Bruce Levin; Myunghee Cho Paik Statistical methods for rates and proportions. john wiley & sons(2013). [Google Scholar]
  13. Prathamesh Kalamkar; Aman Tiwari; Astha Agarwal; Saurabh Karn; Smita Gupta; Vivek Raghavan; Ashutosh Modi Corpus for Automatic Structuring of Legal Documents In: arXiv:2201.13125v2[cs.CL](2022). [Google Scholar]
  14. Lafferty JD; McCallum A; Pereira FCN Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: proceedings of the eighteenth international conference on machine learning, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, ICML 01, pp. 282–289(2001). [Google Scholar]
  15. Nejadgholi I; Bougueng R; Witherspoon S A semi-supervised training method for semantic search of legal facts in canadian immigration cases. In: legal knowledge and information systems–JURIX, pp. 125–134(2017). [Google Scholar]
  16. Pagliardini M; Gupta P; Jaggi M Unsupervised learning of sentence embeddings using compositional n-gram features. In: proceedings of the 2018 conference of the North American chapter of the association for computational linguistics: human language technologies, Vol. 1, pp 528–540(2018). [Google Scholar]
  17. Paheli Bhattacharya; Shounak Paul Kripabandhu Ghosh; Saptarshi Ghosh; Adam Wyner, DeepRhole: deep learning for rhetorical role labeling of sentences in legal case documents.,In: Artifcial Intelligence and Law(2021). [Google Scholar]
  18. Paheli Bhattacharya; Kripabandhu Ghosh; Arindam Pal; Saptarshi Ghosh, Legal Case Document Similarity: You need both network and text.,In: Information Processing and Management(2022). [Google Scholar]
  19. Sanchez G Sentence boundary detection in legal text. In: proceedings of the natural legal language processing workshop 2019:31–38(2019). [Google Scholar]
  20. Saravanan M; Ravindran B; Raman S Automatic identifcation of rhetorical roles using conditional random fields for legal document summarization. In: proceedings of the international joint conference on natural language processing: Vol. 1(2008). [Google Scholar]
  21. Savelka J; Ashley KD Segmenting us court decisions into functional and issue specifc parts. In: legal knowledge and information systems–JURIX, pp. 111–120(2018). [Google Scholar]
  22. Shulayeva O; Siddharthan A; Wyner AZ Recognizing cited facts and principles in legal judgements. Artif Intell Law 25(1):107–126(2017). [Google Scholar]
  23. Venturi G Design and development of temis: a syntactically and semantically annotated corpus of italian legislative texts. In: proceedings of the workshop on semantic processing of legal texts (SPLeT 2012), pp. 1–12(2012). [Google Scholar]
  24. Vijit Malik; Rishabh Sanjay; Shouvik Kumar Guha; Shubham Kumar Nigam; Angshuman Hazarika; Arnab Bhattacharya; Ashutosh Modi Semantic Segmentation of Legal Documents via Rhetorical Roles In: arXiv:2112.01836v1[cs.CL](2021). [Google Scholar]
  25. Walker VR; Pillaipakkamnatt K; Davidson AM; Linares M; Pesce DJ Automatic classifcation of rhetorical roles for sentences: comparing rule-based scripts with machine learning. In: proceedings of the workshop on automated semantic analysis of information in legal texts (with ICAIL)(2019). [Google Scholar]
  26. Wyner A Towards annotating and extracting textual legal case elements. In: CEUR workshop proceedings vol. 605, pp. 9–18(2010). [Google Scholar]
  27. Wyner AZ; Peters W; Katz D A case study on legal case annotation. In: legal knowledge and infor mation systems–JURIX, pp. 165–174(2013). [Google Scholar]
  28. Wyner AZ; Gough F; Lévy F; Lynch M; Nazarenko A On annotation of the textual contents of scottish legal instruments. In: legal knowledge and information systems–JURIX, pp. 101–106(2017). [Google Scholar]
  29. Yamada H; Teufel S; Tokunaga T Neural network based rhetorical status classifcation for Japanese judgment documents. In: legal knowledge and information systems–JURIX, pp. 133–1(2019). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.