In order to understand sparse matrices, we will consider the following real-world scenario: recommending the next item that a supermarket customer is likely to buy, given a set of historical transactions.
In a typical supermarket, there can be millions of customers and thousands of items. Any given user would have bought only a few items among the thousands of items present in the supermarket.
We can represent all the transactions of a supermarket in such a way that all the customers are represented in rows and all the items are represented in columns. The cell values are 1 if the customer bought the item, and 0 otherwise.
In the preceding scenario, we will have a very high majority of zeros and very few ones. This scenario, where the number of ones is extremely low, is called sparsity (sparse number of ones). Hence, the matrix is called a sparse matrix...
