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首页> 外文期刊>International journal of organizational and collective intelligence >RSSMSO Rapid Similarity Search on Metric Space Object Stored in Cloud Environment
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RSSMSO Rapid Similarity Search on Metric Space Object Stored in Cloud Environment

机译：RSSMSO在云环境中存储的度量空间对象上的快速相似性搜索

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This paper involves a cloud computing environment in which the dataowner outsource the similarity search service to a third party service provider. Privacy of the outsourced data is important because they may be confidential data. The data should be made available to the authorized client groups, but not to be revealed to the service provider in which the data is stored. Given this scenario, the paper presents a technique called RSSMSO which has build phase, query phase, data transformation and search phase. The build phase and the query phase are about uploading the data and querying the data respectively; the data transformation phase transforms the data before submitting it to the service provider for similarity queries on the transformed data; search phase involves searching similar object with respect to query object. The RSSMSO technique provides enhanced query accuracy with low communication cost. Experiments have been carried out on real data sets which exhibits that the proposed work is capable of providing privacy and achieving accuracy at a low cost in comparison with FDH
机译：本文涉及一个云计算环境，在该环境中，数据所有者将相似性搜索服务外包给第三方服务提供商。外包数据的隐私性很重要，因为它们可能是机密数据。数据应提供给授权的客户组，而不要透露给存储数据的服务提供商。在这种情况下，本文提出了一种称为RSSMSO的技术，该技术具有构建阶段，查询阶段，数据转换和搜索阶段。构建阶段和查询阶段分别是关于上传数据和查询数据。数据转换阶段先转换数据，然后再将其提交给服务提供商以对转换后的数据进行相似性查询；搜索阶段涉及相对于查询对象搜索相似对象。 RSSMSO技术以较低的通信成本提供了增强的查询准确性。已对真实数据集进行了实验，结果表明与FDH相比，所建议的工作能够以较低的成本提供隐私并实现准确性

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