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Research and Implementation of a System of Webpages Classification Based on User Behavior Analysis

Author: HuangMeiNing
Tutor: LiaoQing
School: Beijing University of Posts and Telecommunications
Course: Communication and Information System
Keywords: User Behavior Analysis Web Page Automatic Categorization Chinese word segmentation CHI Statistics SVM
CLC: TP393.092
Type: Master's thesis
Year: 2011
Downloads: 112
Quote: 0
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Abstract


In recent years, with the rapid development of Internet, network, web vector text messages to a large number of emerging, explosive growth in online information. People to find the information they need is like finding a needle in a haystack, the search engine passive mode can not meet the needs of users. How active mode to meet the user requirements of personalized service, and become one of the challenging issues faced by the new network service system. Based on user behavior analysis and personalized service premise key technologies for web page classification technology research and improvement, and ultimately achieve a text classification system adapted to the web page classification. This paper studies the key technologies include: first, the Chinese word. Original segmentation method and a suitable page text characteristics combined segmentation based on statistical and maximum matching algorithm, the method can identify the the newborn vocabulary pages, and merge the frequent appearance of the word combination. Improved method both to avoid missing classification newborn vocabulary feature space dimension is reduced by combining the word, and to reduce the computational complexity. Second, feature extraction and empowering technology. In this paper, the research and study characteristics selection algorithm and empower the algorithm generally considered better CHI statistical methods suitable for web page classification improved selection algorithm based on the structure of the page CHI statistical characteristics and TD-IDF-CHI Fu the right algorithm. The experimental results show that both pre-processing algorithm in classification accuracy is improved to a certain extent. Based on the above improved algorithm to achieve a web classification module, also designed and implemented a complete user behavior analysis system, the system mainly consists of three modules: data acquisition filter module, web page categorization module and the results of statistical module. The three module functions as follows: First, filter the data acquisition module. Web behavior of the user attribute information is present in the HTTP packet header, to obtain the user's information need to parse HTTP packets and information extraction. The process of data acquisition filter module designed and implemented HTTP packet parsing. Second, Web page classification module is the main object of this paper. The module is based on an improved segmentation algorithm, a preprocessing algorithm and classification better KNN and SVM classification algorithm to achieve the process map page to a specific category. Third, the results statistics module. The module summarizes and updates the classification results of the users to access the web, and is directly connected with the personalized service system directly applied to the results of the analysis of user behavior in personalized service ad feedback. Pages based on user behavior analysis research and achieve classification system applies to the web online classifieds and offline classified two modes, experimental results show that the the preprocessing algorithm improved classification accuracy good correction results statistics module design also obtained good results fully reflect the interest of the user to provide a reference model for personalized service system.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Computer network > General issues > The application of computer network > Web browser
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