| Resumen |
Legal texts consist of a great variety of texts, for example laws, rules, statutes, etc. This kind of documents has as an important feature, that they are strongly linked among them, since they include references from one part to another. This makes it difficult to consult them, because in order to satisfy an information request, it is necessary to gather several references and rulings from a single text, and even with other texts. The goal of this work is to help in the process of consulting legal rulings through their retrieval from a request expressed as a question in natural language. For this, a formal model is proposed; this model is based on a weighted, non-directed graph; nodes represent the articles that integrate each document, and its edges represent references between articles and their degree of similarity. Given a question, this is added to the graph, and by combining a shortest-path algorithm with edge weight analysis, a ranked list of articles is obtained. To evaluate the performance of the proposed model we gathered 8,987 rulings and evaluated the answer to 40 test-questions as correct, incorrect or partial. A lawyer validated the answer to these questions. We compared results with other systems such as Lucene and JIRS (Java Information Retrieval System). © 2013 Springer-Verlag. |
