摘要
针对不同用户对语义Web服务需要的偏好及发现的准确性和高效性的问题,提出了一种支持QoS预测的语义Web服务发现方法。首先,对历史用户按照用户情境进行聚类预处理,然后在每个簇中采用BP神经网络算法为当前用户预测其所需的QoS,匹配了服务的功能性需求后,在候选服务中,按照预测的QoS,为用户推荐相应服务。最后通过实验验证了该方法的可行性和有效性。
According to the different user preferences for semantic Web service and to improve the accuracy and efficiency of discovery, this paper proposes a model for semantic web service discovery to support QoS prediction. First, make pretreatment of Clustering according to the situation for history users, and then use BP neural network algorithm to predict the required QoS for CurrentUser. After matching the functional requirements of the service, according to the prediction of QoS, recommend corresponding service for user. Finally, the feasibility and effectiveness of the method is verified by experiment.
出处
《电脑开发与应用》
2013年第6期51-54,共4页
Computer Development & Applications
