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Supervised Machine Learning for Summarizing Legal Documents [chapter]

Mehdi Yousfi-Monod, Atefeh Farzindar, Guy Lapalme
2010 Lecture Notes in Computer Science  
A commercial system for the analysis and summarization of legal documents provided us with a corpus of almost 4,000 text and extract pairs for our machine learning experiments.  ...  That corpus was pre-processed to identify the selected source sentences in extracts from which we generated legal structured data.  ...  The authors also thank Fabrizio Gotti and Farnaz Shariat for technical support, Vincenzo Mignacca for his meticulous proofreading of the final version of this paper, and reviewers for their comments and  ... 
doi:10.1007/978-3-642-13059-5_8 fatcat:4hmw676gzvectin3lydzg3mvcy

Automatic Identification of Rhetorical Roles using Conditional Random Fields for Legal Document Summarization

M. Saravanan, Balaraman Ravindran, S. Raman
2008 International Joint Conference on Natural Language Processing  
In our approach, we annotate roles in sample documents with the help of legal experts and take them as training data.  ...  The understanding of structure of a legal document and the application of mathematical model can brings out an effective summary in the final stage.  ...  To that end, text summarization is an important step for many of these larger information management goals.  ... 
dblp:conf/ijcnlp/SaravananRR08 fatcat:lx7qhwidqbdnhnj64hch66gpoa

Accounting for Sentence Position and Legal Domain Sentence Embedding in Learning to Classify Case Sentences [chapter]

Huihui Xu, Jaromir Savelka, Kevin D. Ashley
2021 Frontiers in Artificial Intelligence and Applications  
In this paper, we treat sentence annotation as a classification task.  ...  We employ sequence-to-sequence models to take sentence position information into account in identifying case law sentences as issues, conclusions, or reasons.  ...  Legal text summarization by exploration of the thematic structure and argu- mentative roles. In: Text Summarization Branches Out; 2004. p. 27-34. Wyner A, Mochales-Palau R, Moens M, Milward D.  ... 
doi:10.3233/faia210314 fatcat:b573ndi7x5hj3icyrouas4s2au

Applications of Mining Arabic Text: A Review [chapter]

Qasem Al-Radaideh
2020 Recent Trends in Computational Intelligence [Working Title]  
These tasks include Arabic text summarization, which is one of the challenging open areas for research in natural language processing (NLP) and text mining fields, Arabic text categorization, and Arabic  ...  Since the appearance of text mining, the Arabic language gained some interest in applying several text mining tasks over a text written in the Arabic language.  ...  The importance and usage of text summarization Automatic text summarization systems are very significant in various domains such as news, medical, oil and gas, legal, and political domains.  ... 
doi:10.5772/intechopen.91275 fatcat:asmhxsm4brhqrkib2suambvco4

Applications of Text Classification using Text Mining

Mrs. Manisha Pravin Mali, Dr. Mohammad Atique
2014 International Journal of Engineering Trends and Technoloy  
Text classification in text mining is a supervised learning process, which aims to assign a document to one or more predefined categories based on its content.  ...  Text mining is a technology to discover patterns, trends and knowledge which is previously unknown, semiautomatically from huge collections of unstructured text.  ...  Buried in legal information are interpretations of the law in a case, relationships between police reports and written statements, and trends or patterns in society.  ... 
doi:10.14445/22315381/ijett-v13p244 fatcat:7y6x5xijkjf6dlb4vins6fbdyq

A Machine Learning Approach to Identifying Sections in Legal Briefs

Scott Vanderbeck, Joseph Bockhorst, Chad Oldfather
2011 Midwest Artificial Intelligence and Cognitive Science Conference  
Our approach uses learned classifiers in a two-stage process to categorize white-space separated blocks of text.  ...  First, we use a binary classifier to predict whether or not a text block is a section header.  ...  Grover et al. developed a method for automatically summarizing legal documents from the British legal system.  ... 
dblp:conf/maics/VanderbeckBO11 fatcat:o73qomgv35hv7dl7f7ak5a64ta


Roland Vasili, Endri Xhina, Ilia Ninka, Thomas Souliotis
2018 Knowledge International Journal  
This is the first attempt in the field of summarization in Albanian language and there is a high need for future research works in this area.  ...  Text summarization is the process of finding the main source of information, extracting the main important contents and presenting them as a concise text in the predefined template.  ...  At first, the system analyses the main text and then it presents its comprehension from the text in a human understandable form.  ... 
doi:10.35120/kij28072251r fatcat:de3s4vllf5cetlnqunkeojvryi

Text Analytics: the convergence of Big Data and Artificial Intelligence

Antonio Moreno, Teófilo Redondo
2016 International Journal of Interactive Multimedia and Artificial Intelligence  
Currently Text Analytics is often considered as the next step in Big Data analysis.  ...  Several techniques are currently used and some of them have gained a lot of attention, such as Machine Learning, to show a semisupervised enhancement of systems, but they also present a number of limitations  ...  With large texts, text summarization processes and summarizes the document in the time it would take the user to read the first paragraph.  ... 
doi:10.9781/ijimai.2016.369 fatcat:v4e6utdnxrb6hpszmdhidss7g4

Cognitive Category Learning

Rosemary D. Paradis, Jinhong K. Guo, John Olden-Stahl, Jack Moulton
2012 Procedia Computer Science  
This paper describes a cognitive category learning system that uses machine learning and natural language processing (NLP) techniques to categorize unstructured documents or semi-structured objects, such  ...  as emails, which we used in this experiment.  ...  separation 95.3% Automatic Summarization As part of the experiment, we also were developed automatic summarization of the email content.  ... 
doi:10.1016/j.procs.2012.09.052 fatcat:xx7kkbagpzbulacb5usdnqwkbi

A Survey of Text Mining Techniques and Applications

Vishal Gupta, Gurpreet S. Lehal
2009 Journal of Emerging Technologies in Web Intelligence  
In this paper, a Survey of Text Mining techniques and applications have been s presented.  ...  Text Mining is the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources.  ...  An automatic summarization [16] process can be divided into three steps: (1)In the preprocessing step a structured representation of the original text is obtained; (2) In the processing step an algorithm  ... 
doi:10.4304/jetwi.1.1.60-76 fatcat:wx3k6xjfh5dodjewrpu2jgfs4y

Techniques of Big Data Text Summarization

2019 International journal of recent technology and engineering  
Further it describes recent advances in big data text summarization, and then delve into extraction and abstraction-based text summarization.  ...  Vast amount of online information, available in healthcare, social media websites, e-commerce web pages, e-books, legal domain, e-news, etc. has made text processing a vital extent of research.  ...  Also, although it is a far cry, there is certainly a need to have automatic categorization of the similar court cases and their verdicts.  ... 
doi:10.35940/ijrte.d9932.118419 fatcat:aqml62px3vbcxnpaik7oboufrq

Analysis on Text Summarization

Akash Divekar
2022 International Journal for Research in Applied Science and Engineering Technology  
Basically, it is necessary to understand how people summarize the text and build a system based on that.  ...  It consists of selecting sentences and paragraphs that are important in the original text and combining them into a short form. It is mentally simple and easy to use  ...  ACKNOWLEDGEMENTS We thank the Head of Department and all the members of the Master of Computer Application department of the Institute of Management & Computer Studies (IMCOST) for the encouragement that  ... 
doi:10.22214/ijraset.2022.44848 fatcat:q5qriohzpvbkbhhawoinjmbxdu

Generating Value from Textual Discovery [chapter]

Peter Jackson
2007 Lecture Notes in Computer Science  
Fortunately, text mining tools that support the automatic classification, summarization, and linking of documents can be developed and deployed cost effectively.  ...  This paper describes the application of text and data mining techniques to legal information in a manner that enables powerful report generation and document recommendation services.  ...  To most writers, it is either (1) discovering novel patterns from text data, as data mining does for databases, or (2) a preliminary step to data mining, in which you first have to extract the relevant  ... 
doi:10.1007/978-3-540-72588-6_123 fatcat:ccem7bets5hnflvzbmudxcl6zq

Towards Technological Approaches for Concept Maps Mining from Text

Camila Zacche Aguiar, Davidson Cury, Amal Zouaq
2018 CLEI Electronic Journal  
In addition, the categorization has given us objective conditions to establish new specification requirements for a new technological approach aiming at concept maps mining from texts.  ...  From this study, we elaborate a categorization defined on two perspectives, Data Source and Graphic Representation, and fourteen categories.  ...  We aim that the use of an objective categorization to understand and compare approaches in this context is a first step to improve and expand research in the area.  ... 
doi:10.19153/cleiej.21.1.7 fatcat:jacb2ohfs5dfhoh3s7imlxjp34

Summarization, Simplification, and Generation: The Case of Patents [article]

Silvia Casola, Alberto Lavelli
2021 arXiv   pre-print
We survey Natural Language Processing (NLP) approaches to summarizing, simplifying, and generating patents' text.  ...  To the best of our knowledge, this is the first survey of generative approaches in the patent domain.  ...  Few documents are, in fact, as hard to process (for both humans and automatic systems) as patents, with their obscure language and complex discourse structure.  ... 
arXiv:2104.14860v1 fatcat:nc3v6wyimzcblkmdu2da37isiu
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