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首页> 外文期刊>Journal of computational and theoretical nanoscience >GAFY: A Novel Approach for Increased Confidence in Knowledge Based Decision Support System in Online Samples
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GAFY: A Novel Approach for Increased Confidence in Knowledge Based Decision Support System in Online Samples

机译:GAFY:一种新的在线样本中基于知识决策支持系统的信心增加的新方法

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摘要

The online shopping pattern analysis of customers based on their purchase and shopping history mined from browser histories does not provide reliable customer preferences. So a partial and single source dependent pattern analysis will result in inappropriate online suggestions to customersand will end up in customer dissatisfaction and suggestions will be ignored or marked as destructive. Therefore Genetic Algorithm on Fuzzy Inputs is proposed to satisfy customer with the most appropriate suggestions mined from multiple platforms. Our proposed algorithm is implemented and testedusing MATLAB and the results shows that the accuracy is increased reasonably.
机译:基于浏览器历史的购买和购物历史的客户在线购物模式分析不提供可靠的客户偏好。 因此,部分和单一来源依赖模式分析将导致对客户的不适当的在线建议,最终会在客户不满意,建议将被忽略或标记为破坏性。 因此,提出了以多个平台开采的最合适的建议来满足客户的遗传算法。 我们所提出的算法已经实施和测试MATLAB,结果表明,合理提高了准确性。

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