Association rules express the likelihood of co occurrence of features or events in records in a database (e.g. if a patient has characteristics A and B, he or she has an 80% chance of having characteristic C). Data-mining software can automatically identify associations in large data sets. Although many associations are trivial, some indicate causative or "common cause" relationships. Changing associations over time may also provide useful information.