نتایج جستجو برای: association rules mining
تعداد نتایج: 700240 فیلتر نتایج به سال:
Data mining, also known as knowledge discovery in databases, is the process of discovery potentially useful, hidden knowledge or relations among data from large databases. An important topic in data mining research is concerned with the discovery of association rules. The majority of databases are distributed nowadays. In this paper is presented an algorithm for mining fuzzy association rules f...
Discovering association rules and association rules change (ARC) from existing large databases is an important problem. This paper presents an approach based on multi-hash chain structures to mine association rules change from large database with shorter transactions. In most existing algorithms of association rules change, the mining procedure is divided into two phases, first, association rul...
Association rule mining is the most important technique in the field of data mining. The main task of association rule mining is to mine association rules by using minimum support thresholds decided by the user, to find the frequent patterns. Above all, most important is research on increment association rules mining. The Apriori algorithm is a classical algorithm in mining association rules. T...
Many algorithms to mine the association rules are divided into two stages, the first is to find the frequent set; the second is use the frequent set to generate association rules. This proposal discuss the respective characteristics and .shortcoming of the current algorithms to mine association rules and propose another method to mine faster; unlike the other algorithms, this algorithm emphasis...
Association rules is one of data mining methods for discovering knowledge from large amounts of data in databases. In this paper, we propose an intelligent method for discovering association rules, called IMAR. IMAR is designed through three main phases, i.e., preprocessing, processing and post processing. It has been experimented using three domain data sets, i.e., Australian Credit Card (ACC)...
The focus of this paper is the discovery of negative association rules. Such association rules are complementary to the sorts of association rules most often encountered in literatures and have the forms of X→¬Y or ¬X→Y. We present a rule discovery algorithm that finds a useful subset of valid negative rules. In generating negative rules, we employ a hierarchical graph-structured taxonomy of do...
One of the most well-studied problems in data mining is mining for association rules. There was also research that introduced association rule mining methods to conduct classification tasks. These classification methods, based on association rule mining, could be applied for customer segmentation. Currently, most of the association rule mining methods are based on a supportconfidence structure,...
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