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首页> 外文期刊>IEICE Transactions on Information and Systems >On Identifying Useful Patterns to Analyze Products in Retail Transaction Databases
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On Identifying Useful Patterns to Analyze Products in Retail Transaction Databases

机译：识别有用的模式以分析零售交易数据库中的产品

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摘要

Mining correlated patterns in large transaction databases is one of the essential tasks in data mining since a huge number of patterns are usually mined, but it is hard to find patterns with the correlation. The needed data analysis should be made according to the requirements of the particular real application. In previous mining approaches, patterns with the weak allinity are found even with a high minimum support. In this paper, we suggest weignted support affinity pattern mining in which a new measure. weighted supocrt confidence (ws-confidence) is developed to identify correlated pa ten s with the weighted support allinity. To efficiently prune the weak tiffiniry patterns, we prove that the ws-confidence measure satisfies the and-monotone and cross weighted support properties which can be applied to eliminate patterns with dissimilar weighted support levels. Based on the two properties, we develop a weighted support allinity pattern mining algorithm (WSP). The weighted support allinity patterns can be useful to answer the comparative analysis queries such as rinding itemsets containing items which give similar total selling expense levels with an acceptable error range α% and detecting item lists with similar levels of total profits. in addition, our performance study shows that WSP is efficient and scalable for mining weighted support affinity patterns.
机译：在大型事务数据库中挖掘相关模式是数据挖掘中的基本任务之一，因为通常会挖掘大量模式，但是很难找到具有相关性的模式。应根据特定实际应用的要求进行所需的数据分析。在以前的采矿方法中，即使具有较高的最小支持量，也会发现关联度较弱的模式。在本文中，我们建议使用weigned支持亲和力模式挖掘中的一种新措施。建立加权超置信度（ws-confidence）以识别与加权支持关联度相关的十秒。为了有效地修剪薄弱的tiffiniry模式，我们证明了ws置信度度量满足和单调和交叉加权支持特性，可用于消除加权支持级别不同的模式。基于这两个属性，我们开发了加权支持Allinity模式挖掘算法（WSP）。加权支持关联度模式对于回答比较分析查询（例如，包含包含具有可接受的误差范围α％的相似的总销售费用水平的项目的浸洗项目集）以及检测具有相似的总利润水平的项目清单很有用。此外，我们的性能研究表明，WSP在挖掘加权支持亲和力模式方面是高效且可扩展的。

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