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The Method of Mining Inter-transaction Association Rule for Web Usage Mining

Author: QiYanYan
Tutor: RenYongGong
School: Liaoning Normal University
Course: Computer Software and Theory
Keywords: Web usage mining Inter-transaction association rules Cluster analysis The dual policy analysis model Markov model
CLC: TP311.13
Type: Master's thesis
Year: 2011
Downloads: 15
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Abstract


Web Data Mining Web resources and the environment according to the user's browsing behavior extracted and valuable information of interest to users. Web usage mining is an important part of the data mining, the user is the core of Web usage mining. Web usage mining association rules algorithm to obtain meaningful, descriptive model of user behavior and to provide users with guidance forecast experience. Association rules mining algorithm in the previous transaction system analysis and summary, this paper proposes two new transaction association rules mining algorithm: (1) based on the cluster analysis of the transaction association rules mining algorithm, the algorithm uses poly about less class analysis of the initial complex data sets to remove redundant data, reduce the data set to avoid repeatedly scan the database and the generation of a large number of false rules; followed by small data sets obtained after clustering preprocess transaction association rules predictive analysis. The experimental results show that this method than individual inter-transaction association rules method is more efficient, more accurate predictions of user interest. (2) dual policy analysis model based clustering transaction association rules, the algorithm will double strategic interest in the idea of ??the analytical model into the association rule mining algorithm based on cluster analysis Affairs. Firstly, the use of a dual strategy of the integrity of the model to determine the inter-transaction association rules, the initial database is divided into associated libraries and Markku make up for digging holes to avoid the generation of false rules; followed by the use of cluster analysis to remove the associated libraries and Markku irrelevant redundant data to improve the efficiency of the implementation of the algorithm; Finally, clustering preprocess each sub-database transaction association rules to predict and Markov Model. Experimental results show that the algorithm are better than traditional transaction association rules algorithm in terms of accuracy and efficiency of the implementation. With the continuous development of Web technology, the Web server to store the data gradually toward large, multidimensional direction. Web usage mining has raised new challenges, namely how to solve the contradiction between the mining speed and accuracy. Inter-transaction association rules and cluster analysis method of combining both to improve the speed of mining to ensure accuracy, to put forward new and innovative ideas for Web usage mining.

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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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