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An Advanced Research Framework to Investigate Valuable Frequent Itemsets using Mining

机译：使用挖掘调查有价值的频繁项目集的高级研究框架

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摘要

The popularity of market applications including stand-alone and e-commerce have been rapidly growing in the two decades and accumulated mass of data from their customers. The extraction of hidden, predictive knowledge in the form of frequent itemsets from such databases is a crucial task in the Data Mining research. Specifically, identifying valid, previously unkown and potentially useful frequent itemsets is a computationally intensive procedure. Although, extensive studies have been proposed in the literature for extracting frequent itemsets from large database, many of them have focused largely on identifying frequent itemsets based on statistical correlations aamong the items. This situation got the focus of present data mining researchers into the era of Utility Mining. The emerging utility mining not only focuses on frequencies of statistical values among the itemsets but also throw light on the utility associated wit the itemsets and it endorsed as a basic motivation factor for the present study. In addition, utility mining discovers all high utility itemsets beyond the user specified threshold values from large database, push forward towards the present study.
机译：在过去的二十年中，包括独立应用程序和电子商务在内的市场应用程序的普及迅速增长，并且积累了来自客户的大量数据。从此类数据库中以频繁项集的形式提取隐藏的预测知识是数据挖掘研究中的关键任务。特别地，识别有效的，先前未知的和潜在有用的频繁项目集是计算密集的过程。尽管在文献中已经提出了广泛的研究来从大型数据库中提取频繁项集，但是许多研究主要集中在基于项之间的统计相关性来识别频繁项集。这种情况已成为当前数据挖掘研究人员关注的实用采矿的时代。新兴的效用挖掘不仅关注项目集之间统计值的频率，而且还阐明了与项目集相关联的效用，并且它被认可为本研究的基本动机。此外，实用程序挖掘会从大型数据库中发现超出用户指定阈值的所有高实用程序项集，从而推动本研究。

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