Frequent pattern mining in EDGAR log files

Frequent pattern mining – or association rule learning – is a concept from machine learning used to discover strong rules in large databases. Popular applications are for example supermarket transactions: {tooth brush} → {tooth paste}. People who buy tooth brushes are likely to buy toothpaste as well. Another example could be {butter, bread, milk} → {cheese}.