We present a closed set data mining paradigm which is particularly e ective for uncovering the kind of deterministic, causal dependencies that characterize much of basic science. While closed sets have been used before in frequent set data mining, we believe this is the rst algorithm to incrementally combine closed sets one at a time to actually mine associations. Keywords knowledge discovery, concept analysis, closure, incremental, logical implications
John L. Pfaltz, Christopher M. Taylor