Design And Implementation Of Market Hot Spots Planning System Based On Data Mining

Data mining is a hot issue in research of artificial intelligence and database. The purpose of data mining is to extract the implicit, potential useful information and knowledge from the large, incomplete, noisy, fuzzy and random data. The discovered knowledge must be acceptable, understandable, and can be used, but do not require as universal, just required to support a particular problem.Association rules is a kind of important knowledge that exists in the database which can be found. With the continuous development of database and network technology, association rules mining algorithm in data mining is more and more attention, and get more and more widely used. But along with the advance of technology, the shortcoming of traditional association rules mining algorithm is exposed gradually. So the writer chooses this topic for research.The thesis mainly researches the application of data mining technology in the system of market hot spots planning. Therefore, in the process of writing, it not only gives the present research condition and the trend of development in the field of data mining technology, but also gives bottlenecks of Apriori algorithm. So it can make the meaning and feasibility of the topic outstanding. Through analyzing the classical association rules mining algorithm, connecting with the reality of the market hot spots planning system, the writer researched and designed the improved association rules mining algorithm, and applied it to the system’s design.The system adopts Visual Studio.NET as development platform, C# as development language, and designs a dynamic database to implement the market hot spots planning system based on data mining. In this paper the main work and achievements are as follows:1. The analysis shows why we implement the market hot spots planning system based on data mining, the related research status at home and abroad, this system can solve which problems and can realize which functions.2. Introduces the two classic association rule mining algorithm—Apriori algorithm and FP- tree algorithm, and analyzes their advantages and disadvantages.3. Based on the two classical principle of association rule mining algorithm, combined with the bit related operation logic and set theory, the association rule mining algorithm based on linked list is proposed, and carries on the instance analysis and algorithm analysis.4. Build system development environment, design and implement the market hot spots planning system based on data mining, mainly including architecture module, the realization of the function of the various functional modules and database design, and show the user interface system.5. Research the testing of each function module of market hot spots planning system based on data mining, verified the login module, customer management module, product management module and association rules mining module, system through the test and can be put into use.