Research Of Data Mining Algorithms Based On Positive And Negative Association Rules

With the rapid development of information technology, the development of e-commerce and the development of WWW applications, massive amounts of data have been continuously collected in the databases of many application areas, which contain much useful patterns, and it is very important to find the hidden and previously unknown information for these areas, data mining aims at the tasks of the above work.Association rule mining is a form of data mining, association rules has attracted much attention from practitioners and researchers since it was introduced by Agrawal in 1993, This dissertation systematically, deeply, roundly and detailedly studies and analyses the data mining technique, especially the one for association rules. The main contents are listed as follows:Analyse and research of the data mining technique. The appearance of the data mining technique is reviewed in brief first. Based on the basic concepts of data mining, this dissertation classifies and summarizes the objects of data mining, the findable patterns and the common techniques in detail.Analyse and research of the data mining technique for association rules. Based on the basic concepts of the association rules, this dissertation classifies and summarizes its species roundly and summarizes, analyses and studies its typical mining algorithms and these algorithms' basic ideas in detail.Design, analyse and research of Positive and Negative Associate Rule algorithm. This dissertation measures the relationship among items through correlation. Based on the tradition association rules, A method is proposed to calculate the support and confidence of Negative Associate Rule. This dissertation analyzes and research principium of operating and the implement step in detail. An experiment is performed and the experimental results demonstrate that the algorithm is effective.