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Tomas Mikolov, Ilya Sutskever, Kai Chen, G. Corrado, J. Dean (2013)
Distributed Representations of Words and Phrases and their Compositionality
Yoshinobu Kano, Mi-Young Kim, Masaharu Yoshioka, Yao Lu, J. Rabelo, Naoki Kiyota, R. Goebel, K. Satoh (2018)
COLIEE-2018: Evaluation of the Competition on Legal Information Extraction and Entailment
Rie Johnson, Tong Zhang (2014)
Effective Use of Word Order for Text Categorization with Convolutional Neural NetworksArXiv, abs/1412.1058
Ankur Parikh, Shay Cohen, E. Xing (2014)
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)The Association for Computational Linguistics
Aliaksei Severyn, Alessandro Moschitti (2015)
Learning to Rank Short Text Pairs with Convolutional Deep Neural NetworksProceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
A. Wyner, R. Hoekstra (2012)
A legal case OWL ontology with an instantiation of Popov v. HayashiArtificial Intelligence and Law, 20
A. Mandal, Raktim Chaki, S. Saha, Kripabandhu Ghosh, Arindam Pal, Saptarshi Ghosh (2017)
Measuring Similarity among Legal Court Case Documents
Anatoly Getman, V. Karasiuk (2014)
A crowdsourcing approach to building a legal ontology from textArtificial Intelligence and Law, 22
The minimum score of summary phrases is higher than the mean score of document phrases
Yoav Goldberg (2017)
Neural Network Methods for Natural Language ProcessingSynthesis Lectures on Human Language Technologies, -
Ben Hachey, Claire Grover (2004)
A Rhetorical Status Classifier for Legal Text Summarisation
Ben Hachey, Claire Grover (2005)
Automatic legal text summarisation: experiments with summary structuring
Nal Kalchbrenner, Edward Grefenstette, Phil Blunsom (2014)
A Convolutional Neural Network for Modelling Sentences
Filippo Galgani, P. Compton, A. Hoffmann (2012)
Citation Based Summarisation of Legal Texts
Trevor Bench-Capon, M. Araszkiewicz, Kevin Ashley, Katie Atkinson, Floris Bex, Filipe Borges, D. Bourcier, P. Bourgine, Jack Conrad, E. Francesconi, T. Gordon, Guido Governatori, Jochen Leidner, David Lewis, R. Loui, L. McCarty, H. Prakken, Frank Schilder, E. Schweighofer, Paul Thompson, A. Tyrrell, Bart Verheij, Douglas Walton, A. Wyner (2012)
A history of AI and Law in 50 papers: 25 years of the international conference on AI and LawArtificial Intelligence and Law, 20
Qian Chen, Xiao-Dan Zhu, Zhenhua Ling, Si Wei, Hui Jiang, D. Inkpen (2016)
Enhanced LSTM for Natural Language Inference
Omer Levy, Yoav Goldberg (2014)
Dependency-Based Word Embeddings
Filippo Galgani, P. Compton, A. Hoffmann (2012)
Towards Automatic Generation of Catchphrases for Legal Case Reports
Y. Zeng, Ruili Wang, John Zeleznikow, E. Kemp (2005)
Knowledge Representation for the Intelligent Legal Case Retrieval
Mi-Young Kim, Ying Xu, R. Goebel (2012)
Summarization of Legal Texts with High Cohesion and Automatic Compression Rate
A. Wyner (2008)
An ontology in OWL for legal case-based reasoningArtificial Intelligence and Law, 16
P. Jackson, Khalid Al-Kofahi, A. Tyrrell, Arun Vachher (2003)
Information extraction from case law and retrieval of prior casesArtif. Intell., 150
Yoon Kim (2014)
Convolutional Neural Networks for Sentence Classification
(2012)
A (2012b) Towards automatic generation
Quoc Le, Tomas Mikolov (2014)
Distributed Representations of Sentences and Documents
A. Mandal, Kripabandhu Ghosh, Arindam Pal, Saptarshi Ghosh (2017)
Automatic Catchphrase Identification from Legal Court Case DocumentsProceedings of the 2017 ACM on Conference on Information and Knowledge Management
Yang Liu, Meng Zhang (2018)
Neural Network Methods for Natural Language Processing by Yoav GoldbergComputational Linguistics, 44
Vu Tran, Minh Nguyen, K. Satoh (2018)
Automatic Catchphrase Extraction from Legal Case Documents via Scoring using Deep Neural NetworksArXiv, abs/1809.05219
(1999)
Guide to Uniform Production of Judgments. Australian Institute of Judicial Administration
M. Saravanan, Balaraman Ravindran, S. Raman (2009)
Improving legal information retrieval using an ontological frameworkArtificial Intelligence and Law, 17
Jeffrey Pennington, R. Socher, Christopher Manning (2014)
GloVe: Global Vectors for Word Representation
Encoded Summarization for
Encoded summarization: summarizing documents into continuous…
(1999)
Judicial Administration AI (1999) Guide to Uniform Production of Judgments
John Duchi, Elad Hazan, Y. Singer (2011)
Adaptive Subgradient Methods for Online Learning and Stochastic OptimizationJ. Mach. Learn. Res., 12
We present our method for tackling a legal case retrieval task by introducing our method of encoding documents by summarizing them into continuous vector space via our phrase scoring framework utilizing deep neural networks. On the other hand, we explore the benefits from combining lexical features and latent features generated with neural networks. Our experiments show that lexical features and latent features generated with neural networks complement each other to improve the retrieval system performance. Furthermore, our experimental results suggest the importance of case summarization in different aspects: using provided summaries and performing encoded summarization. Our approach achieved F1 of 65.6% and 57.6% on the experimental datasets of legal case retrieval tasks.
Artificial Intelligence and Law – Springer Journals
Published: Dec 25, 2020
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