Paper Info
Title
Abstracting of legal cases: the SALOMON experience
Abstract
The SALOMON project automatically summarises Belgian criminal cases in order to improve access to the large number of existing and future court decisions. SALOMON extracts relevant text units from the case text to form a case summary. Such a case profile facilitates the rapid determination of the relevance of the case or may be employed in text search. Techniques are developed for identifying and extracting relevant information from the cases. A broader application of these techniques could considerably simplify the work of the legal profession. A double methodology was used when developing SALOMON. First, the case category, the case structure and irrelevant text units are identified based on a knowledge base represented as a text grammar. Consequently, general data and legal foundations concerning the essence of the case are extracted. Secondly, SALOMON extracts informative text units of the alleged offences and of the opinion of the court based on shallow statistical techniques. The application of cluster algorithms based on the selection of representative objects has a potential for automatic theme recognition, text abstracting and text linking, even beyond the legal field. Evaluation of the results demonstrates that the SALOMON techniques do not themselves solve any legal questions, but they do guide the user effectively towards relevant texts.
Year
DOI
Venue
1997
10.1145/261618.261643
ICAIL
Keywords
Field
DocType
legal case,salomon experience,knowledge base,sgml
Data mining,SGML,Computer science
Conference
ISBN
Citations 
PageRank 
0-89791-924-6
28
1.42
References 
Authors
20
3
Name
Order
Citations
PageRank
Marie-Francine Moens11750139.27
Caroline Uyttendaele2915.83
Jos Dumortier312014.52