Abstract
This chapter addresses the interesting problem of analyzing multiple databases that do not possess a similar data structure except that there must exist at least one point of contact between any two databases. An analogy is made with different wineries in the same community. Each winery produces its own special wines, and each wine has its own set of characteristics, but they all come from the same geographical area. Hence, one would want to understand the complex interactions that occur among the different wineries. Similarly, different police organizations may have their data stored in databases whose data structures, or the kinds of data placed in the fields that make up the records, differ across the organizations. This chapter is a blend of serious theory and useful application.
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Buscema, M. (2013). Artificial Adaptive System for Parallel Querying of Multiple Databases. In: Buscema, M., Tastle, W. (eds) Intelligent Data Mining in Law Enforcement Analytics. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4914-6_19
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DOI: https://doi.org/10.1007/978-94-007-4914-6_19
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