Implications in Conceptual Scaling
One way of computing dependencies in data set are implications. To extract implications from data sets, we first have to interpret the data on the ordinal level via a method called conceptual scaling. The implication that we find in the scaled data set can have two origins. The first are dependencies in the many-valued data set and the second are artifacts from the scaling process. With your work you develop a method to analyze these sets of implications separately.
Informationen: Johannes Hirth