Abstract
Data is now collected in a variety of commercial and scientific fields in such quantities that the problem of automating the elicitation of meaningful knowledge from data has become pressing. For example, data sets from astronomical observations were once manually scanned by experts searching for anomalies or interesting patterns. However, as Fayyad et al. (1996) note, the manual analysis of data in astronomy is no longer feasible since data sets in this field often exceed many thousands of millions of records.
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© 2006 Springer
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Stranieri, A., Zeleznikow, J. (2006). KNOWLEDGE DISCOVERY FROM LEGAL DATABASES—USING NEURAL NETWORKS AND DATA MINING TO BUILD LEGAL DECISION SUPPORT SYSTEMS. In: Lodder, A.R., Oskamp, A. (eds) Information Technology and Lawyers. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4146-2_4
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DOI: https://doi.org/10.1007/1-4020-4146-2_4
Publisher Name: Springer, Dordrecht
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