A QoS and QoE based Integrated Model for Bidirectional Web Service Recommendation
A QoS and QoE based Integrated Model for Bidirectional Web Service Recommendation
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DOI：
10.23919/pnc.2018.8579474
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发表时间：
2018-10
期刊：
影响因子：
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通讯作者：
Sneh S. Jhaveri;Pooja Soundalgekar;Kevin George;S. Kamath S
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文献类型：
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作者：
Sneh S. Jhaveri;Pooja Soundalgekar;Kevin George;S. Kamath S
对于给定的需求，识别相关的Web服务并推荐最佳的Web服务是面向服务的应用程序开发中的一项重要任务。提出了一种结合服务质量和体验质量的双向Web服务推荐模型。基于服务质量的推荐模型建立在用户满意度的基础上，使用特殊的归一化技术和用户满意度函数(如响应时间和吞吐量)进行计算。在包含用于情感分析的网络服务的正面、负面和中性文本评论的数据集上训练QOE模型，并使用聚类方法将其映射到每个服务的QOS值。这进一步优化了Web服务对消费者的推荐，因为评论的情感评分使用加权平均评分与用户满意度相结合。为了描述Web服务与消费者和提供者与消费者之间的关系，建立了一个立方体模型。为了向消费者推荐服务和向服务提供商推荐潜在消费者，使用了基于混合协同过滤的技术。当仅使用QOS时，以及当QOS和情感分析分数综合起来形成QOE时，所获得的结果显示推荐质量显著提高。
For a given requirement, identifying relevant Web services and recommending the best ones is an important task in Service-oriented application development. In this paper, a composite model that leverages Quality of Service (QoS) and Quality of Experience (QoE) for bidirectional Web service recommendation (bi-WSR) is proposed. The QoS based recommendation model is built on degree of user satisfaction, calculated using a special normalization technique and user satisfaction functions like response time and throughput. The QoE model is trained on a dataset containing positive, negative and neutral textual reviews of web services for sentiment analysis and mapped to each service's QoS values using a clustering method. This further optimizes the recommendation of web services to consumers, as the sentiment score of reviews is integrated with the user satisfaction using weighted average scoring. To describe the relationship between both web services & consumers and providers & consumers, a cube model is built. For recommending services to consumers and recommending potential consumers to service providers, hybrid collaborative filtering based techniques were used. The results obtained when only QoS is used, and when QoS and sentiment analysis scores are integrated to form QoE showed significant improvement in the quality of recommendation.