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Research on Mining User Access Mode Based on Web Logs

Author: XiaCong
Tutor: SunLingFang
School: Jiangsu University of Science and Technology
Course: Management Science and Engineering
Keywords: Web usage mining Web log Association rules User Clustering Behavior patterns
CLC: TP311.13
Type: Master's thesis
Year: 2011
Downloads: 36
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Abstract


With the rapid development of the network and information technology , Web-based applications has covered various aspects of social life , the data on the Web is usually a flood of . These data , compared to the structure and content of the page , the user 's usage patterns more interesting . Access to the user's access patterns , we can achieve a range of applications to improve customer relations : from the optimization of website design based on visitor behavior patterns to design and modify the site structure and layout , allowing users access to the pages of interest to the shortest possible time , optimize service performance ; understand and analyze a user's browsing behavior , found that potential users and user resides ; grasp of user access behavior , organizational decision-makers can design more targeted catalogs, to improve the accuracy of business decisions ; found that the access patterns of individual users , to identify the user's interests , hobbies , habits and needs , the establishment of a personalized user model to provide users with more personalized content and services . User mode information is usually reflected in the Web server log . Web server logging user interaction with the server information to reflect all of the action the user to access the Web site . Analysis of the Web log mining user access behavior mode and hobbies and other useful information , which can understand the behavior of the user's access . Based on the method and process of Web usage mining , the Web server log file as a data source , aimed at mining frequent access path to find the site user access patterns of individual users as well as groups of users . Mining frequent access path for a single user , in detail two representative association rule mining algorithm based on the perspective of association rules useful , the introduction of interesting degree of measurement factor to achieve the improvement of the algorithm ; against groups of users , after a detailed analysis of user clustering process , the navigation path - based clustering algorithm found groups of users access mode . Finally, a user access pattern mining system model framework describes the function of each module and experimental analysis , combined with specific instances of data to illustrate .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
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