The Design And Implementation Of Recommendation System For Bond-type Financial Products

With the development of economic, people’s life quality got better and better, and they have more money than before, which means they can get more resource with their money. According to this phenomenon, a lot of economic products and their transforms are proposed and designed for people with different requests. Both of the customers and the enterprises get benefits from the products. Because of many uncertain factors, the quality of some economic products are not as good as the others. While most of the customers can not tell the difference between the good ones and the bad ones. As a result, our customers lose money.In this article, we did a survey on the current economic products and intend to develop an economic products recommendation system. This system recommends different products to different people according to the historical information and the individual’s request.First we list all the tools and theory with relationship with economic product recommendation system. Then we extend these techniques and proposed our own system. This system is divided into three parts:the ETL process of the initial dataset. the design of recommendation system and the information visualization part. We focus on the last two parts. We make use of information visualization technique to illustrate the recommendations and reveal the relation, mode and pattern hidden in the large dataset. In the recommendation part, we adopt content-based and collaborative algorithms to analyse the dataset and generate the recommendations. We also integrate some useful interaction techniques to help people to adjust the visualization and recommendation process.Now the recommendation system has been finished and performs very well. At one hand, this system saves people’s time and energy to find out the proper products. At the other hand, it provides a very good platform for the enterprises to introduce their products. It is a double win.