Abstract
The progressive deployment of ICT technologies in the courtroom, jointly with the requirement for paperless judicial folders pushed by e-justice plans, are quickly transforming the traditional judicial folder into an integrated multimedia folder, where documents, audio recordings and video recordings can be accessed via a web-based platform. Most of the available ICT toolesets are aimed at the deployment of case management systems and ICT equipment infrastructure at different organisational levels (court or district). In this paper we present the JUMAS system, stemmed from the homonymous EU project, that instead takes up the challenge of exploiting semantics and machine learning techniques towards a better usability of the multimedia judicial folders. JUMAS provides not only a streamlined content creation and management support for acquiring and sharing the knowledge embedded into judicial folders but also a semantic enrichment of multimedia data for advanced information retrieval tasks.
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Fersini, E., Messina, E., Archetti, F., Cislaghi, M. (2013). Semantics and Machine Learning: A New Generation of Court Management Systems. In: Fred, A., Dietz, J.L.G., Liu, K., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2010. Communications in Computer and Information Science, vol 272. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29764-9_26
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DOI: https://doi.org/10.1007/978-3-642-29764-9_26
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