NCR Corporation
Data-Driven Recommendation Engine

Abstract:

Transaction item codes for transactions are mapped to item vectors within multidimensional space. Each transaction defines a plurality of item vectors for transaction item codes that are mapped within the multidimensional space. Any given item vector's positions within the multidimensional space can have distances calculated to other specific item vectors plotted within the multidimensional space. The distances between the other specific item codes and a given item vector's positions represent probabilities that specific items are likely to be associated with the corresponding item associated with the transaction. Item vector distances below a predefined threshold for a given transaction having a given set of items represent items that are not present in the given transaction but should be recommended to be included with the given transaction. Recommendations are sent in real-time during transactions as items in each of the transactions are identified and as combinations of items change within the transactions.