Online grocery shopping becomes more and more popular in recent years. To facilitate the purchase process many online stores provide a shopping recommendation system for their consumers. So far the generic recommendation systems mainly consider preferences of a consumer based on his/her purchase histories. Nevertheless it is noted that there is nothing to do with the right timing to purchase a product from the view point of product replenishment or economic purchasing. Hence we develop a new recommendation scheme especially for online grocery shopping by incorporating two additional considerations i.e. product replenishment and product promotion. We believe that such a new scheme should be able to provide a better recommendation list which fit consumer desires needs and budget considerations and finally boost transactions.
Collaborative filtering-apriori-Multiple Linear regression