PERSO-retailer: Modeling the retailer's business data: Toward recommender system of retailers' marketing plan for personalized CMS

摘要

This research aims to exploring the new research of personalized information access in the context of the online retailing. In this paper, we present PERSO-Retailer Modeler, the first stage in this line of research. We propose to add a new level of personalization in the Content Management System (CMS) application by not only creating an e-commerce website to run the retailer's business but by recommending the most relevant marketing plan to ensure the business success. In this perspective, the main advantage of our approach is to transform the traditional CMS into a personal assistant that fits the retailer's selling strategies for product offerings. Our methodology is based on hierarchical clustering of retailer's model, then using the frequent pattern mining techniques to identify common strategies used in a given cluster. The preliminary finding of our experimentation prototyping encourage us to proceed to the next stage of the research which is to propose an evaluation framework as well as exploring further data-mining techniques.