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Service recommendation based on description reconstruction in cloud manufacturing

机译:基于描述重建在云制造中的服务推荐

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摘要

Cloud manufacturing has become an important development trend in the manufacturing industry. Manufacturing companies package their resources and capabilities as manufacturing services and publish on cloud manufacturing service system. With the rapid increase of a number of services being published on the service system, information overload becomes an issue. To identify functional requirements accurately and create service compositions in a timely manner, effective manufacturing service recommendation algorithm is urgently needed. Most traditional recommendation methods ignore the evolving characteristics of the cloud manufacturing service system and rely on initial static service descriptions. These descriptions are usually neither comprehensive nor pertinent in describing service application scenarios. To solve such issues, a novel method of Time-aware Targeted Reconstructing Service Descriptions (T-TRSD) is proposed in this paper. T-TRSD aims to reconstruct service descriptions by adding service composition descriptions. The evolving characteristics of services are also taken into consideration by the algorithm. This model complements the potential application scenarios of services, identifies the application scenario of the specific requirement and gives this scenario a higher weight. Based on service descriptions reconstructed by T-TRSD, a new manufacturing service recommendation strategy is offered. Comprehensive experiments show that this method brings a better recommendation performance.
机译:云制造已成为制造业的重要发展趋势。制造公司将其资源和能力置于制造服务,并在云制造服务系统上发布。随着在服务系统上发布的许多服务的快速增加,信息过载成为一个问题。为了准确识别功能性要求并及时创建服务组合,迫切需要有效的制造服务推荐算法。大多数传统推荐方法忽略了云制造服务系统的不断变化特性,并依赖于初始静态服务描述。这些描述通常在描述服务应用程序方案时既不是全面的也不是相关的。为了解决这些问题,本文提出了一种新颖的时代目标重建服务描述(T-TRSD)。 T-TRSD旨在通过添加服务构图描述来重建服务描述。算法还考虑了服务的不断发展特征。该模型补充了服务的潜在应用方案,识别特定要求的应用方案,并给出了这种情况更高的权重。基于T-TRSD重建的服务描述,提供了一种新的制造服务推荐策略。综合实验表明,该方法带来了更好的推荐性能。

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