Performance Analysis Of The Mobile Internet Business

The mobile Internet technology increasingly mature, the rapid growth of application types and constantly enrich the user scale, and accelerate the growth of the amount of data. A large number of hidden information associated with business performance in vast amounts of data, which can be by analysis of the difference in a variety of business performance. Data mining technology plays a very important role in the process of analysis. Using data mining technology, extract the information with effective performance characteristics from massive data, classify and analyze the business with different performance characteristics at the same time, achieving the performance analysis of the mobile internet business, which is conducive to the balanced network load and improve network resource utilization.In this paper, a system used to study the performance of the mobile Internet business analysis is designed. The analysis system consists of three modules:data acquisition module, data preprocessing module and data mining modules. Handle the effective information with identification, selection, collection and storage in data information acquisition module using JPCAP middleware technology and database storage technology to handle. The data preprocessing module contains processes on the effective information data including purification, integration and transformation. Data mining module, using the k-means clustering analysis in data mining algorithm to cluster analysis of operating performance attributes of the business. The traditional k-means clustering analysis algorithm uses the randomized method to determine the initial centers, so it will cause the results of clustering error and randomness. Therefore the method of determining the initial centers is improved, and verified by experiments that the improved algorithm is feasible and the results of cluster analysis are valid. Finally, the improved algorithm is applied to data mining analysis system module.