A Data Mining Framework for Optimal Product Selection in Convenience Stores
نویسندگان
چکیده
Previous research in the field of data mining has demonstrated that the technique of association rules is very well suited to find patterns in the purchase behaviour of customers. However, practitioners occasionally criticize that it is not straightforward to adopt the discovered knowledge for concrete retail marketing decision-making. This is partially due to the difficult integration of retail domain knowledge into the mining process which sometimes causes the discovered knowledge to be sterile. This paper makes an attempt at integrating category management knowledge into the knowledge discovery process in order to obtain more useful results, i.e. results that can better be used for concrete decision-making in retailing. More specifically, an integer programming model for product selection is proposed which takes into account cross-selling effects between products and also enables the retailer to integrate category management knowledge into the model. First results on real-world retail data demonstrate the success of the approach.
منابع مشابه
Mining Customer Knowledge for a Recommendation System in Convenience Stores
Taiwan’s rapid economic growth with increasing personal income leads increasing numbers of young unmarried people to eat out, and shopping at convenience stores for food is indispensable to the lives of these people. Thus, it is an essential issue for convenience store owners to know how to accurately market appropriate products and to choose effective endorsers for brands or products in order ...
متن کاملOptimal Feature Selection for Data Classification and Clustering: Techniques and Guidelines
In this paper, principles and existing feature selection methods for classifying and clustering data be introduced. To that end, categorizing frameworks for finding selected subsets, namely, search-based and non-search based procedures as well as evaluation criteria and data mining tasks are discussed. In the following, a platform is developed as an intermediate step toward developing an intell...
متن کاملUsing Association Rules for Product Assortment Decisions in Automated Convenience Stores
Association rules is a recent data mining technique to discover affinities, in large transaction databases, between items frequently purchased together. It has been claimed that the discovery of frequent sets of items is well suited for applications of market basket analysis to discover regularities in the purchase behaviour of customers. In this study, we integrate the discovery of frequent it...
متن کاملOptimal Feature Selection for Data Classification and Clustering: Techniques and Guidelines
In this paper, principles and existing feature selection methods for classifying and clustering data be introduced. To that end, categorizing frameworks for finding selected subsets, namely, search-based and non-search based procedures as well as evaluation criteria and data mining tasks are discussed. In the following, a platform is developed as an intermediate step toward developing an intell...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2000