Automatic Knowledge Acquisition for Creating Nuclear Juridical Lexica

Abstract Knowledge acquisition constitutes the bottleneck for the creation of legal expert systems. Our prototype CONCAT deals with the problem that the information is formalised to a certain degree by use of legal language. This task is performed in that the process of creating a selective thesaurus for a nuclear juridical lexicon is supported which can be used for automatic indexing and document classification. This selectivity is obtained by distinguishing between precise legal terms and words with fuzzy meanings. The resulting thesaurus can thus represent automatically the expert knowledge of a lawyer about legal terminology. Therefore, CONCAT can be used as a tool for the semi-automatic creation of a legal knowledge base for the automatic representation of the structure and the contents of the documents. As structuring techniques we applied cluster analysis and neural networks. The cluster algorithm creates satisfying results but turned out to be very sensitive as concerns the fine tuning of parameters. The neural network achieves comparable quality without the need for any adaptation.

[1]  C. Hepburn.  Information retrieval system. , 1978, Journal of clinical orthodontics : JCO.

[2]  Carole D. Hafner.  An information retrieval system based on a computer model of legal knowledge , 1981 .

[3]  Michael McGill,et al.  Introduction to Modern Information Retrieval , 1983 .

[4]  George R. Cross,et al.  Representation of legal knowledge for conceptual retrieval , 1985, Inf. Process. Manag..

[5]  Vijay V. Raghavan,et al.  On modeling of information retrieval concepts in vector spaces , 1987, TODS.

[6]  J. Bing,et al.  Designing text retrieval systems for conceptual searching , 1987, ICAIL '87.

[7]  Richard K. Belew,et al.  A connectionist approach to conceptual information retrieval , 1987, ICAIL '87.

[8]  Gerard Salton,et al.  A Simple Blueprint for Automatic Boolean Query Processing , 1988, Inf. Process. Manag..

[9]  M. E. Maron,et al.  Full-text information retrieval: Further analysis and clarification , 1990, Inf. Process. Manag..

[10]  Cees Groendijk,et al.  Networks at work: a connectionist approach to non-deductive legal reasoning , 1991, ICAIL '91.

[11]  Chris D. Paice,et al.  A thesaural model of information retrieval , 1991, Inf. Process. Manag..

[12]  Les Johnson,et al.  Conceptual information retrieval in litigation support systems , 1991, ICAIL '91.

[13]  Judith P. Dick.  Representation of legal text for conceptual retrieval , 1991, ICAIL '91.

[14]  W. Bruce Croft,et al.  A Comparison of Text Retrieval Models , 1992, Comput. J..

[15]  Trevor J. M. Bench-Capon.  Neural networks and open texture , 1993, ICAIL '93.

[16]  Werner Winiwarter,et al.  Refining the Selectivity of Thesauri by Means of Statistical Analysis , 1993, Terminology and Knowledge Engineering.

[17]  E. Schweighofer,et al.  Intelligent Information Retrieval : KONTERM-Automatic Representation of Context Related Terms within a Knowledge Base for a Legal Expert System , 1994 .

[18]  Teuvo Kohonen,et al.  The self-organizing map , 1990, Neurocomputing.