The User Attention Analysis And Individualized Study Based On "Chinese Scienecpaper Online"

With the increased number of papers in "Chinese Scienecpaper Online ", how to find the paper which has the higher attention become the key issues. This will benefit to learn what research are the contents of the current mainstream research and the areas of concern to scholars. Can also according to the issues of concern to users quickly find the content meet the requirements of the user personalized from the mass data, to achieve to show different users the effect of different pages. So as to achieve the user's personalized information services. Existing information services system has obvious defects. For example scattered resources, search focus, emerged of the same display for all users, and among groups, different sources of information using different service mechanisms, different services use different identity proof mechanisms and so on.The key to solving these problems is make Internet from a passive acceptance of the user's request into the initiative to understand the needs of users, to achieve Internet system provide users active information services. How to obtain useful information effectively from vast amounts of data, how to improve the intelligence of information retrieval and push, and how to meet the individual needs of various users and so on, is a new information service system to be solved in time. Personalized information service is the main mode of future information services; it implements the information to find someone, according to the needs of users to provide service.This paper make the basic data obtained from "Chinese Scienecpaper Online" as a training set, get the weight of each parameter in the user attention formula by genetic algorithm, determining the user attention formula, get the user attention of the paper, further get the keyword attention, to analyze the attention of research area, and through the analysis of user information to determine user needs, thereby establishing the user requirements model, then on this basis combination of user customization, provide users with personalized information services.