Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Can legal knowledge be derived from legal texts?
ICAIL '93 Proceedings of the 4th international conference on Artificial intelligence and law
Self-organizing maps
Finding legally relevant passages in case opinions
Proceedings of the 6th international conference on Artificial intelligence and law
Proceedings of the 6th international conference on Artificial intelligence and law
Toward adding knowledge to learning algorithms for indexing legal cases
ICAIL '99 Proceedings of the 7th international conference on Artificial intelligence and law
A learning technique for legal document analysis
ICAIL '99 Proceedings of the 7th international conference on Artificial intelligence and law
Legal Knowledge Representation: Automatic Text Analysis in Public International and European Law
Legal Knowledge Representation: Automatic Text Analysis in Public International and European Law
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Some Remarks on Vector Representations of Legal Documents
DEXA '00 Proceedings of the 11th International Workshop on Database and Expert Systems Applications
Self organization of a massive document collection
IEEE Transactions on Neural Networks
On original generation of structure in legal documents
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
A relatedness analysis approach for regulation comparison and e-rulemaking applications
dg.o '05 Proceedings of the 2005 national conference on Digital government research
Automatic semantics extraction in law documents
ICAIL '05 Proceedings of the 10th international conference on Artificial intelligence and law
Legal information retrieval and application to e-rulemaking
ICAIL '05 Proceedings of the 10th international conference on Artificial intelligence and law
Is linguistic information relevant for the classification of legal texts?
ICAIL '05 Proceedings of the 10th international conference on Artificial intelligence and law
Mapping regulations to industry-specific taxonomies
Proceedings of the 11th international conference on Artificial intelligence and law
Artificial Intelligence and Law - Legal knowledge extraction and searching & legal ontology applications
Relating taxonomies with regulations
dg.o '08 Proceedings of the 2008 international conference on Digital government research
Regulation retrieval using industry specific taxonomies
Artificial Intelligence and Law
Semantic Processing of Legal Texts
Topological pattern discovery and feature extraction for fraudulent financial reporting
Expert Systems with Applications: An International Journal
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The huge text archives and retrieval systems of legal information have not achieved yet the representation in the well-known subject-oriented structure of legal commentaries. Content-based classification and text analysis remains a high priority research topic. In the joint KONTERM, SOM and LabelSOM projects, learning techniques of neural networks are used to achieve similar high compression rates of classification and analysis like in manual legal indexing. The produced maps of legal text corpora cluster related documents in units that are described with automatically selected descriptors. Extensive tests with text corpora in European case law have shown the feasibility of this approach. Classification and labeling proved very helpful for legal research. The Growing Hierarchical Self-Organizing Map represents very interesting generalities and specialties of legal text corpora. The segmentation into document parts improved very much the quality of labeling. The next challenge would be a change from tf × idf vector representation to a modified vector representation taking into account thesauri or ontologies considering learned properties of legal text corpora.