Research On Business Intelligence Architecture And Data Mining Technology Based On Industrial Chain Collaboration Platform

The automobile industrial chain is a huge network, which is composed of automobile manufacturers, suppliers, dealers and service providers etc. ASP-based industrial chain collaborated platform is an effective way to cut the operation cost of industrial chain, and realize the complicated information exchange in industrial chain collaboration, and the platform has become a major way to enhance the competitiveness of automobile industry. The successful implementation of the public technology service platform improves the collaborative efficiency of upstream and downstream business in automobile industrial chain, lowers the cost of business information exchange, transmission and acquisition, and accelerates the accumulation of business data.With the accumulation of enterprise's business data and competition of market environment, how to make use of these data to create value becomes the next issue needed to be considered by the enterprises. The enterprises hope to transform these data into reliable information, find the potential rule, improve the quality of decision, grasp and discover the market opportunity, and enhance the enterprise competitiveness. But the traditional information system can not meet the new requirement of enterprise. However, the business intelligence based on data warehouse, online analytical processing and data mine brings new hope for enterprise. Business intelligence is a process based on the extraction of mass data and knowledge re-integration, this process combines closely with knowledge share and knowledge creation, accomplishes the transformation from information to knowledge, and helps the enterprise policy maker make a timely, correct, feasible and effective decision, and finally strengthens the enterprise's competitiveness.Based on automobile industrial chain collaborative ASP platform developed by Sichuan Institute of Manufacturing Information, which is supported by National technology project " highly competitive business-oriented promotion and application of industrial chain collaborative technology integration (2006BAF01A37)", following aspects of research work are finished.1) With the successful promotion and implementation of automobile industrial collaborative ASP Platform, The accumulation of enterprise data has increased day by day. Face to the increased competition in the market environment, the managers of enterprise consider to implement the BI system based on current situation, to meet the requirements of information decision. Combined with the feature of automobile industrial chain and customer requirements, the solution and architecture of BI system based on automobile industrial chain collaborative platform is put forward.2) Faulty analysis of vehicles is to find the association rules between faulty accessories and vehicle mileage, time, region, brand of accessory, related faulty accessory, which is to improve the performance of the overall design. The core algorithm of association rules mining is to find frequent item set. The candidate item set generation principle, used by the classical association rules mining algorithm Apriori, determines that scanning the database of this algorithm is too frequently when finding the frequent item set. FP-Growth algorithm of none candidate item set reduces the I/O data exchange greatly through finding frequent set by FP-tree. But the scale of FP-tree is related to data characteristic. Constructing FP-tree based on the memory is not realistic when data set is big and too sparse. And the congenital deficiency of the pruning algorithm causes that the frequent set is difficult to reuse when the database changes. For the issue mentioned above, frequent set discovering and updating algorithm based on matrix are put forward.3) The customers are the important strategic resources of enterprises; efficient customer relation management is on the basis of solid customer segmentation. And the main way to realize the customer segmentation is customer cluster. Design an efficient, accurate customer segmentation cluster algorithm, which is the key to realize customer segmentation of automobile collaborative industrial chain platform. Based on the problems of slow convergence rate and difficulty on initial cluster center selection of mixed data cluster algorithm-FKP, GA-FKP algorithm is raised in this thesis. This algorithm use GA to search the initial clustering center needed by FKP algorithm, optimize the chromosome with FKP algorithm and avoid premature convergence.GA_FKP cluster mining algorithm is an improved algorithm of mixed data cluster, and it has generality. FIMABoFM frequent itemset find algorithm find the frequent itmeset from a new perspective, and make up for the shortcomings of existing algorithms. Automobile industrial chain collaborative platform-based BI system architecture realizes the seamless integration and program resource sharing to the original platform, minimizes the workload of system development, and provide a reference method to information system BI integration of other small-and-medium-sized enterprises...