Research And Design Of A Recommendation System Based On Exhibition Hall Scheme Marketing

With the development of exhibition hall scheme network marketing, their schemes and clients had rapidly grown in recent years. In the condition, exhibition hall scheme clients must waste much time to glance over many schemes before they find their fancies. These similar purchase processes often happen in exhibition hall marketing processes, which lead the information overload problems to bore the clients. And much client loss was resulted from the inefficient marketing processes. Although in the recommendation systems for the exhibition hall scheme marketing, E-commerce researchers carried out some research. But the general problems of traditional recommendation systems had included poor accuracy, low efficiency, low customer satisfaction, and low information availability. The personalized recommendation system of exhibition hall scheme marketing includes personalized recommendation algorithms, information mining and matching algorithms. The above technologies give a new framework to deal some recommendation problems. The system integrates and uses use the client’s preference, attribute, and content and so on. Based on mining the client preferences and requirements from two aspects of the internal and external systems, the recommendation system gives clients some recommended lists including their needs and interest. And the thesis consists of as following:1. The section.1 gives a literature review of the recommendation system, focusing on the recommendation system, the marketing work as a part of the previous and existing problems. Then based on the analysis of the recommendation system of exhibition hall scheme marketing, the section gives some demand and key problem solutions, and put forward some ideas and technical route of the system development;2. The section.2 presents the overall structures and working flows of the recommendation system. And the section gives its functional design requirements, design requirements and performance requirements, the five parts, the system includes: internal information discovery module, external information discovery module, data management module, service module and a recommendation system recommended the database; design, several key processes of the system are mainly includes: internal and external information mining, data processing, recommended practice and so on;3. The section.3 carries on the detailed design to the recommendation system. Their keys are still the client demand and the exhibition hall description, extraction, information fusion, and finally the section gives the scheme and customer demand matching implementation details, the interface and the key flow chart;4. 4. The section.4 researches on the recommendation system key technology research and do some analysis of the simulation results. Then, the key technologies include as following exhibition hall history scheme recommendation algorithms and exhibition hall new scheme algorithm. And the tests consist of a subjective test and a considerable test. The simulation results shows that the system has higher customer satisfaction, precision, recall rate, less system resource occupies.