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Study on the Approach of Association Rules Based on Triangular Fuzzy Number

Author: XuZuo
Tutor: FengZhiHong
School: Lanzhou Jiaotong University
Course: Applied Computer Technology
Keywords: Data Mining Association rules Apriori algorithm Triangular fuzzy numbers PRETI Customer Satisfaction
CLC: TP311.13
Type: Master's thesis
Year: 2007
Downloads: 139
Quote: 0
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Abstract


Data mining is the rapid development in recent years , information processing technology . Data mining is implied from the large number of incomplete noise , fuzzy and random data , extract in which people do not know in advance , but potentially useful information and knowledge of the process . Association rule mining as an important area of data mining research branch , its task is to find all strong association rules to meet the support threshold and confidence threshold . In recent years, the association rule mining has become a hot topic in data mining . Apriori algorithm is a classical algorithm of association rule mining . However, in the specific association rules mining applications often encounter the following two questions : ( 1 ) traditional Apriori algorithm for all items without any distinction : a consistent treatment of , in the process of in association rules found in the transaction database , will not miss some important patterns it ? ( 2) If you consider the various decision criteria (weight ) is different , the term weight how to consider and divided ? response to these two questions proposed based on a triangular fuzzy number Apriori algorithm . And PRETI ( Platform for Research and Experiments in the Treatment of Information ) Apriori algorithm and the Apriori algorithm based on triangular fuzzy number comparison than Apriori does verify that the algorithm can effectively solve the above two issues . To illustrate the effectiveness and feasibility of the algorithm . Attention increasingly mature extension and application of the theory of data mining and data warehousing , customer satisfaction analysis based on data mining . Customer satisfaction is the psychological experience of customers after the end of the process of consumption and intuitive fuzzy set theory just to meet the people of this preference . So combine intuitive fuzzy set theory , the nature of the α - cut set the Apriori algorithm principle proposed algorithm mining association rules for customer satisfaction . Example of analysis and research . Validation the scientific and effectiveness of the algorithm .

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