Abstract
Recently there has been an exponential growth of the number of publicly available legal resources. Portals allowing users to search legal documents, through keyword queries, are now widespread. However, legal documents are mainly stored and offered in different sources and formats that do not facilitate semantic machine-readable techniques, thus making difficult for legal stakeholders to acquire, modify or interlink legal knowledge. In this paper, we describe Solon, a legal document management platform. It offers advanced modelling, managing and mining functions over legal sources, so as to facilitate access to legal knowledge. It utilizes a novel method for extracting semantic representations of legal sources from unstructured formats, such as PDF and HTML text files, interlinking and enhancing them with classification features. At the same time, utilizing the structure and specific features of legal sources, it provides refined search results. Finally, it allows users to connect and explore legal resources according to their individual needs. To demonstrate the applicability and usefulness of our approach, Solon has been successfully deployed in a public sector production environment, making Greek tax legislation easily accessible to the public. Opening up legislation in this way will help increase transparency and make governments more accountable to citizens.
Subject
Computational Mathematics,Computational Theory and Mathematics,Numerical Analysis,Theoretical Computer Science
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