Sometimes we are so overwhelmed by the masses of data that must be managed that it is difficult to see the many ways that we can learn from information. However, the ability to link individual objects together into patterns and networks is a valuable enhancement to many knowledge-discovery applications.

The key to this kind of analysis is the ability to look at lots of things, figure out the sets of attributes that distinguish them, and then find the small collections of things that can be linked together based on attribute similarities. The operative word here is similarity. While it is relatively easy to link two records when most of the values are identical, it is much more of a challenge to connect two data instances when their values don't match exactly, but upon inspection, clearly refer to the same thing.

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