01536nas a2200157   4500008004100000245008700041210006900128260000900197520094200206100002301148700002101171700002101192700002101213700002001234856012401254       2017                        eng d00aMarket Basket Prediction using User-Centric Temporal Annotated Recurring Sequences0 aMarket Basket Prediction using UserCentric Temporal Annotated Re  bIEEE3 aNowadays, a hot challenge for supermarket chains is to offer personalized services to their customers. Market basket prediction, i.e., supplying the customer a shopping list for the next purchase according to her current needs, is one of these services. Current approaches are not capable of capturing at the same time the different factors influencing the customer’s decision process: co-occurrence, sequentuality, periodicity and recurrency of the purchased items. To this aim, we define a pattern named Temporal Annotated Recurring Sequence (TARS). We define the method to extract TARS and develop a predictor for next basket named TBP (TARS Based Predictor) that, on top of TARS, is able to understand the level of the customer’s stocks and recommend the set of most necessary items. A deep experimentation shows that TARS can explain the customers’ purchase behavior, and that TBP outperforms the state-of-the-art competitors.1 aGuidotti, Riccardo1 aRossetti, Giulio1 aPappalardo, Luca1 aGiannotti, Fosca1 aPedreschi, Dino  uhttps://kdd.isti.cnr.it/publications/market-basket-prediction-using-user-centric-temporal-annotated-recurring-sequences