Design And Implementation Of Bio-pesticides Intelligent Recommendation System

With the arrival of the 21 st century, the globe has already been in the era of informatization. As one of the dominant industries of the 21 st century, information services are leading the unceasing development of global e-commerce, and making it continuously improve. With the utilization and popularization of Internet, e-commerce is popular all over the world because it is fast, cheap(low-cost) and convenient to(for) people to use at any space and time(regardless of time or place). The e-commerce has been developed rapidly in recent years, and its scale of market is expanding. In 2012, the deal sizes of China’s e-commerce market are up to ￥7.85 trillion, with year-on-year growth 30.83%. For enterprises and users, because of the more and more e-commerce selections, the e-commerce structure becomes particularly complicated at the same time. Firstly, faced with so much commercial information, users will find it is more difficult to find suitable products. Secondly, for the enterprises, how to let users to discover their needed goods quickly and then boosting sales is also a thorny problem. From the enterprise’s perspective, intelligent recommendation system provides customers with real-time recommendation. It is also increasing the loyalty and satisfaction of customers while promoting the sale of goods.Data Mining is a non-trivial process of revealing the implicit, unknown and potentially valuable information from the vast data in the database. Data Mining is a process of decision support. Based on machine learning, pattern recognition, artificial intelligence, database technology, visualization technology, mathematical statistics, and so on, it digs out potential patterns with the highly automated analysis of the data of the enterprise and inductive reasoning to help policymakers adjust the marketing strategy and reduce the risk and then make right decisions. This dissertation analyzes user’s interests and consumer behavior of the B2C(Business- to- Customer) website,using the Data Mining technology to design and implement an e-commerce recommendation system--- biological pesticide intelligent recommendation system. Biological pesticide intelligent recommendation system is a large e-commerce platform which can provide multiple functions, such as enterprise’s online trading, display of products, commodity recommendation, and the release of information and so on. This dissertation starts from the basic survey of the e-commerce recommendation system to look into the architecture of the recommendation system, the procedure of recommendation, structure and the common recommended algorithm more deeply, and then designs the biological pesticide intelligent recommendation system based on user’s behavior. Finally, it implements and tests the biological pesticide intelligent recommendation system.The contribution of this dissertation lies in implementing biological pesticide intelligent recommendation system by combining relatively complete recommendation system thought in e-commerce field with biological pesticide e-commerce transaction information data. Biological pesticide intelligent recommendation system uses Visual Studio 2010 as a development platform and programming language uses c #. At present, the biological pesticide of intelligent recommendation system has been already invested in market application.The biological pesticide intelligent information platform lays on the distributed database. More importantly, it is able to be expended more conveniently, avoiding unnecessary waste when upgrading hardware. The whole system adopts Visual Studio 2010 as the develop platform and c# programming language. At present, biological pesticide intelligent information platform has been put into market applications successfully.