Abstract
We have designed a system to support collaborative legal case reasoning and building. The design is based on our understanding of the corporate litigation domain acquired through analysis of the literature, interviews of various parties involved in corporate litigation processes, and studies of the commercial tools already available. In this paper we illustrate the designed system and in particular the interaction modes that it supports that we believe address a number of the requirements that emerged through our analysis. We also describe its main components and their integration, including a knowledge model that represents the domain, and a natural language processing component for extracting semantic information. A description of a prototype system is also provided.
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References
Ait-Mokhtar, S., Chanod, J.P., Roux, C.: Robustness beyond Shallowness: Incremental Deep Parsing. J. Nat. Lang. Eng. 8(2-3), 121–144 (2002)
Ashley, K.D., Rissland, E.L.: A Case-Based Approach to Modeling Legal Expertise. IEEE Intelligent Systems 3(3), 70–77 (1988)
Ashley, K.D., Aleven, V.: Reasoning Symbolically about Partially Matched Cases. In: Pollack, M.E. (ed.) 15th Int. Joint Conf. on Artificial Intelligence, vol. 1, pp. 335–341. Ed. Morgan Kaufmann Publishers, San Francisco (1997)
Attfield, S., Blandford, A.: E-discovery Viewed as Integrated Human-Computer Sensemaking: The Challenge of ‘Frames’. In: 2nd Int. DESI Workshop (2008)
Attfield, S., Blandford, A., De Gabrielle, S.: Investigations within Investigations: a Recursive Framework for Scalable Sensemaking Support. In: CHI 2008 Workshop on Sensemaking (2008)
Attfield, S., Blandford, A.: Looking for Fraud in Digital Footprints: Sensemaking with Chronologies in a Large Corporate Investigation. Working paper, UCL Interaction Centre: London, UK (2009)
Bier, E.A., Ishak, E.W., Chi, E.: Entity Workspace: An Evidence File That Aids Memory, Inference, and Reading. In: Mehrotra, S., Zeng, D.D., Chen, H., Thuraisingham, B., Wang, F.-Y. (eds.) ISI 2006. LNCS, vol. 3975, pp. 466–472. Springer, Heidelberg (2006)
BLAZEDS, http://opensource.adobe.com/wiki/display/blazeds/BlazeDS (last accessed in July 2009)
Branting, L.K.: Representing and Reusing Explanations of Legal Precedents. In: 2nd Int. Conf. on Artificial intelligence and Law (ICAIL), pp. 103–110. ACM, NY (1989)
Brüninghaus, S., Ashley, K.D.: Progress in Textual Case-Based Reasoning: Predicting the Outcome of Legal Cases from Text. In: Cohn, A. (ed.) 21st National Conference on Artificial Intelligence, vol. 2, pp. 1577–1580. AAAI Press (2006)
CASEMAP, LexisNexis, articles, http://www.casesoft.com/training/articles.asp (last accessed in February 2011)
Castellani, S., Grasso, A., Benedetti, V., Lagos, N., Hairon, N.: A Semantics-Based Approach to Guide Formulation of Questions for Documentary Reconstruction Activities. Accepted and Presented at the 4th Int. Conf. on Advances in Semantic Processing, SEMAPRO 2010 (2010)
Electronic Discovery Reference Model, http://edrm.net (last accessed April 29, 2011)
JENA, http://jena.sourceforge.net/ (last accessed in July 2009)
Lagos, N., Segond, F., Castellani, S., O’Neill, J.: Event Extraction for Legal Case Building and Reasoning. In: Shi, Z., Vadera, S., Aamodt, A., Leake, D. (eds.) IIP 2010. IFIP AICT, vol. 340, pp. 92–101. Springer, Heidelberg (2010)
Maxwell, K.T., Oberlander, J., Lavrenko, V.: Evaluation of Semantic Events for Legal Case Retrieval. In: WSDM 2009 Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR 2009), pp. 39–41. ACM, New York (2009)
Noel, L., Azemard, G.: From Semantic Web Data to Inform-Action: a Means to an End. In: Workshop SWUI (Semantic Web User Interaction), CHI 2008, Florence, Italie, April 5-10 (2008)
Pioch, N.J., Everett, J.O.: POLESTAR – Collaborative Knowledge Management and Sensemaking Tools for Intelligence Analysts. In: CIKM 2006, pp. 513–521. ACM (2006)
Privault, C., O’Neill, J., Renders, J.-M., Ciriza, V.: A New Tangible User Interface for Machine Learning Document Review. Artificial Intelligence and Law 18(4), 459–479 (2010); Special Issue on “E-Discovery”, Ashley, K.D., Baron J.R., Conrad, J.G. (guest eds.)
Sheth, A., Arpinar, B., Kashyap, V.: Relationships at the Heart of Semantic Web: Modeling, Discovering, and Exploiting Complex Semantic Relationships. Technical Report, LSDIS Lab, Computer Science, Univ. of Georgia, Athens GA (2002)
Stasko, J., Gorg, C., Liu, Z.: Jigsaw: supporting investigative analysis through interactive visualisation. Information Visualisation 7, 118–132 (2008)
Weber-Lee, R., Barcia, R.M., da Costa, M.C., Rodrigues Filho, I.W., Hoeschl, H.C., D’Agostini Bueno, T.C., Martins, A., Pacheco, R.C.: A Large Case-Based Reasoner for Legal Cases. In: Leake, D.B., Plaza, E. (eds.) ICCBR 1997. LNCS, vol. 1266, pp. 190–199. Springer, Heidelberg (1997)
Wright, W., Schroh, D., Proulx, P., Skaburskis, A., Cort, B.: The Sandbox for Analysis - Concepts and Methods. In: CHI 2006. ACM (2006)
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Castellani, S., Lagos, N., Hairon, N., Grasso, A., Martin, D., Segond, F. (2013). A System to Support Legal Case Building and Reasoning. In: Fred, A., Dietz, J.L.G., Liu, K., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2011. Communications in Computer and Information Science, vol 348. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37186-8_14
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DOI: https://doi.org/10.1007/978-3-642-37186-8_14
Publisher Name: Springer, Berlin, Heidelberg
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