The Association Rule Mining Study For Furniture Accessory Sale Industry

Recent years the competitive pressure in sales industry of furniture accessory has increased. No longer does purely traditional method help retailers gain further market percentage and profit margin. Association rules mining is a key issue in data mining. It discovers and analyses the associations among different sets of data items. By introducing the association rules mining technology into the sales industry of furniture accessory, the charactertistcs and associations of the sales staticitics can be obtained, and the potential purchase customes and purchase needs can be grasped in view to formulate relevant sales strategy and procurement strategy.This paper investigates the application of association rules mining technology in the furniture accessory sales industry, and probe into the association rules through brief analysis and application design. In this paper, project background of current mining is introduced, and the key issues and situation at home and abroad of association rules mining technology have been specified. Following that the key concept and principle involved in the association rules mining technology will be introduced, especially the overall design and specification details regarding the data mining procedure. Later in this paper, there is the requirement analisys, which provides details of the sales data charactertistics,function requirement, methods requirement, and other requirements. Following that is the system design of current mining. The mining will be specified in terms of data circulation, process design and operation, technical consideration, database table design, and etc. Examples regarding current mining will be cited. In the following detailed design session, the code implementation of the current mining will be introduced. Specifically, method procedure of the 3 main class-Utility, Rule, and DBAdmin-will be introduced. In the last, the final result demonstration and analysis will be displayed. The association rules will be briefly concluded and demonstrated. Detailed analysis and application design regarding the association rules will be provided.