Design And Implementation Of Statistics And Analysis Software For Wireless Search Behavior Of Users

With the rapid development of mobile Internet, people are getting used to search through the mobile side, resulting in a large number of user behavior and search logs every day, these data can be used to analyze the user’s some common behavior, it can be judged by analyzing user what needs are, and improve our products, increase user stickiness mobile applications, allowing more users to accept and use, to give data to support the project manager at the time of project requirements.This thesis discusses through, the online log of wireless search statistics and analysis, some of the more fragmented user behavior log statistics to quantify the numbers, then these numbers concatenated into user behavior trajectories through a large number of user behavior track statistics, the statistics will generally several user behavior very similar clustering, according to the main features of these clustering analysis of the extent of use of the product for each functional user, and finally then these statistics and analysis of the data through a software show.Which used to handle large logs, including the URL anti-cheating design and implementation of user behavior and the use of cluster analysis according to the log. URL anti-cheating design is the online logs will be analyzed in thought content to weed out interference analysis, mainly used in the search function of log. In addition also uses a clustering operation targeted at improved algorithm, using this algorithm will classify the different user behavior, dig out the user’s preferences, habits and other indicators. In addition, the software also includes data presentation module part, it is the analysis of user behavior in the whole process of data and conclusions were side by statistics and analysis carried out to show the end user behavior data show platform will be processed online log, classification, storage, according to the data needs to show.By studying this thesis, the design, implementation and testing, also being able to use clustering algorithm and analysis of user behavior in-depth research, the results of the study show through in the software to give the user needs the most immediate feedback to achieve a research purposes subject and provide data to support the new features of the product.