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Implementation of Adaptive Framework and WS Ontology for Improving QoS in Recommendation of WS

机译:改进框架和WS本体学改进QoS的建议

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With the advent of more users accessing internet for information retrieval, researchers are more focused in creating system for recommendation of web service(WS) which minimize the complexity of selection process and optimize the quality of recommendation. This paper implements a framework for recommendation of personalized WS coupled with the quality optimization, using the quality features available in WS Ontology. It helps users to acquire the best recommendation by consuming the contextual information and the quality of WS. Adaptive framework performs i) the retrieval of context information ii) calculation of similarity between users preferences and WS features, similarity between preferred WS with other WS specifications iii) collaboration of web service ratings provided by current user and other users. Finally, WS quality features are considered for computing the Quality of Service. The turnout of recommendation reveals the selection of highly reliable web services, as credibility is used for QoS predication.
机译:随着更多用户访问Internet获取信息检索的用户来临,研究人员更专注于创建系统以获取Web服务(WS)的建议,这最大限度地减少了选择过程的复杂性并优化了推荐的质量。本文利用WS本体中可用的质量功能,实现了个性化WS推荐的框架,该框架与质量优化相结合。它可以帮助用户通过消耗上下文信息和WS的质量来获取最佳推荐。自适应框架执行i)上下文信息II的检索II)用户偏好与WS特征之间的相似性,与其他WS规格III的优选WS之间的相似性)由当前用户和其他用户提供的Web服务额定值的协作。最后,考虑计算服务质量的WS质量特征。推荐推荐器显示了选择高度可靠的Web服务,因为可信度用于QoS预测。

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