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首页> 外文期刊>International Journal of Innovative Computing Information and Control >A NEW FRAMEWORK OF MINING ASSOCIATION RULES WITH TIME-WINDOWS ON REAL-TIME TRANSACTION DATABASE
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A NEW FRAMEWORK OF MINING ASSOCIATION RULES WITH TIME-WINDOWS ON REAL-TIME TRANSACTION DATABASE

机译：实时交易数据库中带有时间窗口的采矿关联规则的新框架

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This paper dedicates efforts to discover the part-time association rules in real-time transactional database by extending the traditional minsup-minconf based framework to a new one - the minsup, minconf and minwin based framework. We propose a more general form for association rule, i.e., the Association Rule with Time-Windows (ARTW), to properly integrate the temporal association rales together with the normal ones. New notions like Frequent Itemset with Time-Windows (FITW) are also defined, and an Apriori-like algorithm, named TW-Apriori, is developed to fast generate the FITWs. Computational experiments are conducted on two datasets - a synthetic dataset and a real database. Both experiments show that large number of ARTWs ignored previously can be discovered under the new framework; many of them are even very strong rules and valuable for market decisions. The efficiency of the proposed TW-Apriori algorithm is also proven feasible since it can finish the calculation within one minute and the length of the calculation time is nearly proportional to the number of ARTWs found.
机译：本文致力于通过将传统的基于minsup-minconf的框架扩展到新的基于minsup，minconf和minwin的框架，来发现实时事务数据库中的兼职关联规则。我们提出了一种更通用的关联规则形式，即带有时间窗口的关联规则（ARTW），以将时间关联规则与正常规则正确地集成在一起。还定义了带有时间窗口的频繁项目集（FITW）等新概念，并开发了一种称为TW-Apriori的类似于Apriori的算法来快速生成FITW。在两个数据集上进行了计算实验-合成数据集和真实数据库。两项实验均表明，在新框架下可以发现大量先前被忽略的ARTW。其中许多规则甚至非常严格，对市场决策具有重要意义。 TW-Apriori算法的效率也被证明是可行的，因为它可以在一分钟内完成计算，并且计算时间的长度几乎与所发现的ARTW的数量成正比。

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