On Mining Ordering Rules

Abstract

Many real world problems deal with ordering of objects instead of classifying objects, although majority of research in machine learning and data mining has been focused on the latter. In this paper, we formulate the problem of mining ordering rules as finding association between orderings of attribute values and the overall ordering of objects. An example of ordering rules may state that “if the value of an object x on an attribute a is ordered ahead of the value of another object y on the same attribute, then x is ordered ahead of y”. For mining ordering rules, the notion of information tables is generalized to ordered information tables by adding order relations on attribute values. Such a table can be transformed into a binary information table, on which any standard data mining algorithm can be used.