Survey on Privacy Preserving Association Rule Data Mining

G. Navale, S. Mali
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引用次数: 21

Abstract

The progress in the development of data mining techniques achieved in the recent years is gigantic. The collative data mining techniques makes the privacy preserving an important issue. The ultimate aim of the privacy preserving data mining is to extract relevant information from large amount of data base while protecting the sensitive information. The togetherness in the information retrieval with privacy and data quality is crucial. A detailed survey of the present methodologies for the association rule data mining and a review of the state of art method for privacy preserving association rule mining is presented in this paper. An analysis is provided based on the association rule mining algorithm techniques, objective measures, performance metrics and results achieved. The metrics and the short comings of the various existing technologies are also analysed. Finally, the authors present various research issues which can be useful for the researchers to accomplish further research on the privacy preserving association rule data mining.
隐私保护关联规则数据挖掘研究综述
近年来,数据挖掘技术的发展取得了巨大的进步。协同数据挖掘技术使隐私保护成为一个重要的问题。隐私保护数据挖掘的最终目的是从海量数据库中提取相关信息,同时保护敏感信息。在信息检索中,隐私性和数据质量的一致性至关重要。本文对当前的关联规则数据挖掘方法进行了详细的综述,并对保护隐私的关联规则挖掘的最新方法进行了评述。基于关联规则挖掘算法技术、客观度量、性能指标和获得的结果进行了分析。分析了各种现有技术的指标和不足。最后,作者提出了一些值得研究的问题,这些问题可以为研究人员在保护隐私的关联规则数据挖掘方面的进一步研究提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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