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A Method of Eliminating Redundant Rules and Its Application

Author: WangNa
Tutor: YeZuo
School: Dalian University of Technology
Course: Information management and e-government
Keywords: Association rule mining Redundant rules Priori knowledge Noumenon
CLC: TP311.13
Type: Master's thesis
Year: 2011
Downloads: 21
Quote: 0
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Abstract


The redundancy rules exist is one of the reasons that cause the King quantitative association rule generation . Redundant rules are usually consistent user known a priori knowledge , or with mining rules express the same information , such rules can not bring new information for the user , does not make sense for decision support . Kind of meaningless rules exist not only caused by the excavation waste of resources , the more influence the selection and use of interesting rules , reduce the effectiveness of the mining results . In response to these problems , the paper concluded on the basis of the research review and a clear definition of redundant rules for deletion of redundant rules , a priori knowledge of the basic characteristics of the redundancy rules decision Theorem and Lemma . On this basis , a new redundant rules deletion methods , and one of the core algorithm designed and written in pseudo-code . The method uses a priori knowledge of the inevitability characteristics , using both a priori knowledge and excavated confidence for the 100% rule (special-rule) frequent itemsets judge , capable of carrying out prior to the calculation of the degree of confidence avoids the generation of redundant rules . In order to facilitate the application and testing of the method , this paper design and initial realization of association rule mining into the a priori knowledge of the prototype system . The system on the basis of the original association rule mining system ontology search function and redundant rules deletion function , a priori knowledge into the judgment of redundant rules , can be more effectively the deletion meaningless rules . Finally , the system is used in public security and criminal case information analysis . 100% of a priori knowledge and confidence association rules generated redundant rules into the a priori knowledge of redundant rules deletion attempt , delete redundant rules less research provides a new way of thinking and methods . This study comes from the practical problems of the project , and the research results into practice , after a preliminary verification , achieved a certain effect , to prove the effectiveness of the method .

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