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Data Mining Association Rules algorithm and applied research

Author: LiuFang
Tutor: LuKui
School: Anhui University of Technology
Course: Applied Computer Technology
Keywords: Data Mining Association rules Apriori FP-growth BMSL_Apriori
CLC: TP311.13
Type: Master's thesis
Year: 2010
Downloads: 66
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Abstract


Today, people 's ability to grasp the data has been increasing. Faced with massive data , people are more concerned about hiding behind the important information in the data , not the data itself. Data mining to meet our needs , it is important to help us find the data useful tools for knowledge . Association rule is an important branch of data mining , digging out large-scale transaction database association rules for solving practical problems in different fields plays a very important role. In this thesis, association rules algorithm and its application . Firstly, the paper systematically elaborated data mining and association rules relevant theoretical knowledge for the study of the content in full swing and lay a solid theoretical foundation . Secondly , the paper by pointing out the classical algorithm for mining frequent itemsets Apriori algorithm performance bottleneck problem that scan the database and may produce large candidate set for the new algorithm to find the entrance. Thus , the thesis of improved Apriori algorithm to do the following : First, from the perspective of the database to generate a Boolean matrix L1 and L2, breaking the Apriori algorithm to generate Lk intrinsic mode ; then prove conclusion \-1 ∞ L1 instead Lk-1 ∞ Lk-1 \Therefore, the comprehensive work of this thesis, the improved algorithm BMSL_Apriori Apriori algorithm (Boolean Matrix Simplified Linked_Apriori algorithm ) . First, the algorithm through BMSL_Apriori theoretical analysis, we can see that the algorithm can not only reduce the number of scanning the database and to some extent to avoid the generation of a large set of candidates , but also to reduce the algorithm's time and space overhead. Then , we have to adopt specific experiments further demonstrated BMSL_Apriori efficiency of the algorithm is indeed superior to Apriori algorithm and other algorithms. Finally, better hardware and software environment and with the real part of the supermarket transaction database data , the paper uses Microsoft SQL Server 2005 and VB.NET as the development platform to build a simple association rule mining system, BMSL_Apriori algorithm is applied to the associated rules generated by the mining results once again proved that the algorithm is better than Apriori algorithm and other algorithms have indeed made good mining results.

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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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