Traditional E-Commerce applications have evolved in the last few years due to the growth in the mobile environment, creating a new research area known as U-Commerce. The application of these techniques in the banking environment has been a direct outcome of the desire to enhance services offered to end users. In this article, we present a context-aware mobile recommender system based on real banking data provided by a well-known Spanish bank. The data were composed of customer profiles, credit card transactions and information about places where bank clients have previously spent their money. The system model and its architecture are described, taking into account social, mobility and ubiquitous requisites to generate personalised recommendations. The mobile prototype deployed in the bank was evaluated in a survey among 100 users, with good results regarding trust, usefulness and effectiveness.
목차
Abstract I. INTRODUCTION II. RELATED WORK AND PROBLEM STATEMENT III. MODEL FOR GENERATING CONTEXT-AWARE RECOMMENDATIONS USING BANKING DATA A. Phase I: Social Context Generation B. Phase II: Location Context Filtering C. Phase III: User Context FilteringThe final process to achieve IV. ARCHITECTURE AND IMPLEMENTATION A. Banking Data Anonymisation B. Recommender C. Web Service D. Mobile Client V. EVALUATION AND RESULTS A. Social Clusters B. User Acceptance VI. DISCUSSION VII. CONCLUSION AND FUTURE WORK REFERENCES BIOGRAPHIES
키워드
mobile recommendercontext-awarebanking data miningcustomer segmentationU-CommerceE-Commerce
저자
Daniel Gallego [ Departamento de Ingeniería de Sistemas Telemáticos, Universidad Politécnica de Madrid, Madrid, Spain ]
Gabriel Huecas [ Departamento de Ingeniería de Sistemas Telemáticos, Universidad Politécnica de Madrid, Madrid, Spain ]