Research on information fusion method for mobile electronic commerce based on improved Monte Carlo algorithm under big data environment

Information of mobile e- commerce has increased dramatically and it highlights the characteristics of the user's location information under big data environment. For huge amounts of data under big data environment, how to take advantage of user's location information to mine potentially useful information quickly and efficiently for users, and provide users with useful decision support services, which become one of key research direction in mobile e-commerce recent years . This paper puts forward an improved Monte Carlo algorithm- fast Monte Carlo algorithm on the basis of the traditional Monte Carlo algorithm, which effectively solve particle degradation problems in the traditional algorithm. Finally, the paper makes simulation experiment, compares the traditional information fusion method and shows that the fusion method has higher accuracy, at the same time reducing the complexity of the algorithm. It makes mobile e-commerce platform can more accurately predict user behavior information, better service to provide decision support.