Abstract
Exploratory data analysis seems to be a good tool for the acquisition and representation of the inherent knowledge in legal texts. The main difficulty besides the necessary input is the analysis of the various text and document structures. In our prototype CONCAT we use neural network technology to learn about the relations within the concept and document space of an existing domain. The results are quite encouraging because with existing input data a usable representation of the knowledge space can be obtained.
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© 1996 Springer-Verlag Berlin Heidelberg
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Winiwarter, W., Schweighofer, E., Merkl, D. (1996). Knowledge acquisition in concept and document spaces by using self-organizing neural networks. In: Wermter, S., Riloff, E., Scheler, G. (eds) Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing. IJCAI 1995. Lecture Notes in Computer Science, vol 1040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60925-3_39
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DOI: https://doi.org/10.1007/3-540-60925-3_39
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