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Service Requirement Pattern Elicitation Approach with a Case Study in Pharmaceutical Retail Service Market

机译:制药零售服务市场案例研究的服务要求模式诱因方法

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Every day, the services or composite services satisfy billions of customers' requirements. However, these requirements are not explicit to the service providers, because people always make their decisions randomly or with specific reasons that are not announced directly online. Therefore, digging user interest (portrait) became a trendy measure for Web personalized recommendation. However, user requirement is not only a collection of user interests. It will be more comprehensive, if it contains the mode of user demand occurrence and the trend of user preference evolution. This paper proposes a novel approach based on Artificial Neural Network (ANN) to elicit the service requirement patterns and detect the individual preference evolution under these patterns. A case study is performed in pharmaceutical retail service market to verify this approach.
机译:每天,服务或综合服务满足数阵客户的要求。但是,这些要求没有明确到服务提供商,因为人们始终随机作出决定,或者在没有直接在线宣布的具体原因。因此,挖掘用户兴趣(肖像)成为Web个性化推荐的时尚措施。但是,用户要求不仅是一个用户兴趣的集合。如果它包含用户需求的模式和用户偏好演变的趋势,它将更全面。本文提出了一种基于人工神经网络(ANN)的新方法,以引出服务需求模式并检测这些模式下的个体偏好演变。在制药零售服务市场进行案例研究以验证这种方法。

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