Mining Top-k Fault Tolerant Association Rules by Redundant Pattern Disambiguation in Data Streams

作     者：You Yuyang Zhang Jianpei.College of Computer Science and Technology Harbin Engineering University Harbin HLJ P.R.ChinaYang Zhihong Institute of Medicinal Plant Development CAMS and PUMC Beijing P.R.ChinaLiu Guocai Center for Space Science and Applied Research Chinese Academy of Sciences Beijing P.R.China 

会议名称：《2010 International Conference on Intelligent Computing and Cognitive Informatics (ICICCI 2010)》

会议日期：2010年

学科分类：08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

关 键 词：negative itemset top-k fault tolerant association rule redundant pattern data stream 

摘      要：The real-world data may be usually polluted by uncontrolled factors or contained with ***-tolerant frequent pattern can overcome this *** may express more generalized information than frequent pattern which is absolutely *** present research is integrated with previous research into an integrity new method,called TopNFTDS,to discover fault-tolerant association rules over *** can discover top-k true fault-tolerant rules without minimum support threshold and minimum confidence threshold specified by *** extend the negative itemsets to fault-tolerant space and disambiguate redundant patterns by this *** results show that the developed algorithm is an efficient method for mining top-k fault-tolerant association rules in data streams.