Tutorial on Association Rules

Good piece in KDNuggets,  the approach is useful because it is transparent and thus easily visualized. Here is a further technical definition,  from the approach of set mining and rule generation.  Note this applies in many domains.  We used this to generate initial sample expert rule sets.  The method can be extending to the idea of a knowledge graph.  Below the tutorial introduction:

Association Rules and the Apriori Algorithm: A Tutorial
A great and clearly-presented tutorial on the concepts of association rules and the Apriori algorithm, and their roles in market basket analysis.

The (an Example) Problem

When we go grocery shopping, we often have a standard list of things to buy. Each shopper has a distinctive list, depending on one’s needs and preferences. A housewife might buy healthy ingredients for a family dinner, while a bachelor might buy beer and chips. Understanding these buying patterns can help to increase sales in several ways. If there is a pair of items, X and Y, that are frequently bought together:

Both X and Y can be placed on the same shelf, so that buyers of one item would be prompted to buy the other.

Promotional discounts could be applied to just one out of the two items.
Advertisements on X could be targeted at buyers who purchase Y.
X and Y could be combined into a new product, such as having Y in flavors of X.
While we may know that certain items are frequently bought together, the question is, how do we uncover these associations?

Besides increasing sales profits, association rules can also be used in other fields. In medical diagnosis for instance, understanding which symptoms tend to co-morbid can help to improve patient care and medicine prescription.

Definition

Association rules analysis is a technique to uncover how items are associated to each other. There are three common ways to measure association. .... "