Pattern mining terminology

We will start with a set of items I = {a1, ..., an}, which serves as the base for all the following concepts. A transaction T is just a set of items in I, and we say that T is a transaction of length l if it contains l item. A transaction database D is a database of transaction IDs and their corresponding transactions.

To give a concrete example of this, consider the following situation. Assume that the full item set to shop from is given by I = {bread, cheese, ananas, eggs, donuts, fish, pork, milk, garlic, ice cream, lemon, oil, honey, jam, kale, salt}. Since we will look at a lot of item subsets, to make things more readable later on, we will simply abbreviate these items by their first letter, that is, we'll write I = {b, c, a, e, d, f, p, m, g, i, l, o, h, j, k, s}. Given these items, a small transaction database D could look as follows:

Transaction ID Transaction
1 a, c, d, f, g, i, m, p
2 a, b, c, f, l, m, o
3 b, f, h, j, o
4 b, c, k, s, p
5 a, c, e, f, l, m, n, p
Table 1: A small shopping cart database with five transactions
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