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BP Network Based Users’interest model in Mining WWW Cache

Wuhan University Journal of Natural Sciences 2006年第1期11卷 243-247页

作者： ZHANG Wei-feng XU Bao-wen ZHANG Xiao-fang CUI Zi-feng ZHOU Xiao-yu Department of Computer Science and Technology Nanjing University o[ Posts and Telecommunications Nanjing 210003 JiangsuChina Jiangsu Institute of Software Quality Nanjing 210096 JiangsuChina Department of Cornputer Science and Engineering Southeast University Nanjing 210096 Jiangsu China

By analyzing the WWW Cache model, we bring forward a user-interest description method based on the fuzzy theory and user-interest inferential relations based on BP（baek propagation） neural network. By this method, the users＇ interest in the WWW cache can be described and the neural network of users＇ interest can be constructed by positive spread of interest and the negative spread of errors. This neural network can infer the users＇ interest. This model is not the simple extension of the simple interest model, but the round improvement of the model and its related algorithm.

关键词： WWW Internet interest model neural network data mining

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维普期刊数据库

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Research on Bayesian Network Based User's interest model

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Wuhan University Journal of Natural Sciences 2007年第5期12卷 809-813页

作者： ZHANG Weifeng XU Baowen CUI Zifeng XU Lei Department of Computer Science and Engineering Nanjing University of Posts and Telecommunications Nanjing 210003 JiangsuChina School of Computer Science and Engineering Southeast University Nanjing 210096 Jiangsu China Jiangsu Institute of Software Quality Nanjing 210096 Jiangsu China

It has very realistic significance for improving the quality of users＇ accessing information to filter and selectively retrieve the large number of information on the Internet. On the basis of analyzing the existing users＇ interest models and some basic questions of users＇ interest （representation, derivation and identification of users＇ interest）, a Bayesian network based users＇ interest model is given. In this model, the users＇ interest reduction algorithm based on Markov Blanket model is used to reduce the interest noise, and then users＇ interested and not interested documents are used to train the Bayesian network. Compared to the simple model, this model has the following advantages like small space requirements, simple reasoning method and high recognition rate. The experiment result shows this model can more appropriately reflect the user＇s interest, and has higher performance and good usability.

关键词： Bayesian network interest model feature selection

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维普期刊数据库

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Development and Implementation of Intelligent Mathematics Teaching System Based on Individualized Learning model

Development and Implementation of Intelligent Mathematics Te...

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作者： Wang Yu Neusoft Institute Guangdong

This paper inherits the advantages of the existing intelligent teaching system for mathematics and improves it by individualized learning model.A personalized intelligent teaching system of mathematics in primary schools based on EGL is studied and ***,the whole process of WEB2.0 program based on EGL language design is discussed based on in-depth learning,and its rationality and feasibility are *** the specific business needs of personalized intelligent teaching are discussed and ***,by the implementation of the system,a relatively comprehensive system function and performance test is carried out,which proves that the scheme can effectively enhance the humancomputer interaction experience of the system and improve the real-time performance of system.

关键词： mathematics teaching deep learning interest model EGL

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USERS' TWO-DIMENSIONAL interest AND ITS STORAGE METHOD

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Journal of Electronics(China) 2002年第4期19卷 399-402页

作者： XuBaowen ZhangWeifeng DepartmentofComputerScienceandEngineering SoutheastUnivNanjing210096 StateKeyLaboratoryofSoftwareEngineering WuhanUniversityWuhan430072

The users' interest can be mined from the web cache and can be used widely. The interest can be specialized by the two-tuple (term, weight) in the simple interest model, in which the association relations are not mined, and then the interest cannot be associated in expressing the users' interest. Based on analyzing the WWW cache model, this letter brings forward a twodimensional interest model and gives the interrelated methods on how to store the two-dimensional interest model effectively.

关键词： WWW Internet interest model Data mining Cache

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维普期刊数据库

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