Elements of information theory
Elements of information theory
A comparison of classifiers and document representations for the routing problem
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Machine Learning
The split-up system: integrating neural networks and rule-based reasoning in the legal domain
ICAIL '95 Proceedings of the 5th international conference on Artificial intelligence and law
The effectiveness of machine learning techniques for predicting time to case disposition
Proceedings of the 6th international conference on Artificial intelligence and law
Finding factors: learning to classify case opinions under abstract fact categories
Proceedings of the 6th international conference on Artificial intelligence and law
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
A learning technique for legal document analysis
ICAIL '99 Proceedings of the 7th international conference on Artificial intelligence and law
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
Automatic categorization of case law
Proceedings of the 8th international conference on Artificial intelligence and law
Automatic text representation, classification and labeling in European law
Proceedings of the 8th international conference on Artificial intelligence and law
A machine learning approach to prior case retrieval
Proceedings of the 8th international conference on Artificial intelligence and law
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Feature Selection for Unbalanced Class Distribution and Naive Bayes
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Predicting outcomes of case based legal arguments
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
Classification and clustering for case-based criminal summary judgments
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
PGR: portuguese attorney general's office decisions on the web
INAP'01 Proceedings of the Applications of prolog 14th international conference on Web knowledge management and decision support
A next step towards automated modelling of sources of law
Proceedings of the 12th International Conference on Artificial Intelligence and Law
Automatically classifying case texts and predicting outcomes
Artificial Intelligence and Law
Machine Learning versus Knowledge Based Classification of Legal Texts
Proceedings of the 2010 conference on Legal Knowledge and Information Systems: JURIX 2010: The Twenty-Third Annual Conference
Artificial Intelligence and Law
Semantic Processing of Legal Texts
Semantic indexing of legal documents
Semantic Processing of Legal Texts
Automated classification of norms in sources of law
Semantic Processing of Legal Texts
Clustering and categorization of Brazilian portuguese legal documents
PROPOR'12 Proceedings of the 10th international conference on Computational Processing of the Portuguese Language
Knowledge acquisition for categorization of legal case reports
PKAW'12 Proceedings of the 12th Pacific Rim conference on Knowledge Management and Acquisition for Intelligent Systems
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Text classification is an important task in the legal domain. In fact, most of the legal information is stored as text in a quite unstructured format and it is important to be able to automatically classify these texts into a predefined set of concepts.Support Vector Machines (SVM), a machine learning algorithm, has shown to be a good classifier for text bases [12]. In this paper, SVMs are applied to the classification of European Portuguese legal texts - the Portuguese Attorney General's Office Decisions - and the relevance of linguistic information in this domain, namely lemmatisation and part-of-speech tags, is evaluated.The obtained results show that some linguistic information (namely, lemmatisation and the part-of-speech tags) can be successfully used to improve the classification results and, simultaneously, to decrease the number of features needed by the learning algorithm.