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AN INTELLIGENT SERVICE RECOMMENDATION MODEL FOR SERVICE USAGE PATTERN DISCOVERY IN SECURE CLOUD COMPUTING ENVIRONMENT

机译:安全云计算环境中服务使用模式发现的智能服务推荐模型

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With the increase in the usage of web services in all business activities, the enormous amount of data is created and stored on different cloud servers. It is a challenging task to recommend the appropriate web services according to the demands of the user. The web recommendation techniques mainly concentrate on the mining of the association patterns among the web services from the historical compositions. But, the negative patterns denote the incorrect combination of web services. An accurate service recommendation model is presented by combining the positive patterns with the negative patterns in the large web service network. This paper proposed an intelligent service recommendation model for service usage pattern discovery in secure cloud computing environment. A RuleScore algorithm is proposed for predicting the future service collaboration based on the mined rules. The experiments on the real-time and synthetic datasets show that the proposed model ensures effective recommendation of web services in a large-scale network.
机译:随着所有业务活动中Web服务使用率的增加,大量数据被创建并存储在不同的云服务器上。根据用户的需求推荐适当的Web服务是一项艰巨的任务。 Web推荐技术主要集中在从历史构成中挖掘Web服务之间的关联模式。但是,否定模式表示Web服务的错误组合。通过结合大型Web服务网络中的积极模式和消极模式,提出了一种准确的服务推荐模型。针对安全云计算环境下的服务使用模式发现,本文提出了一种智能服务推荐模型。提出了一种RuleScore算法,用于基于挖掘的规则来预测未来的服务协作。在实时和综合数据集上的实验表明,该模型可确保在大型网络中有效推荐Web服务。

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