不确定QoS偏好下以QoS为中心的多样化业务推荐

Guosheng Kang, Jianxun Liu, Buqing Cao, Yong Xiao
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引用次数: 9

摘要

随着SOA(面向服务的体系结构)的广泛采用,Internet上出现了大量的Web服务。找到所需的服务成为一项挑战。因此,服务推荐成为缓解用户服务选择困难的首要研究课题。现有的Web服务推荐方法采用效用函数或天际线技术,并假设用户可以提供数字QoS(服务质量)首选项。然而,在实践中,用户(甚至是专业用户)很难在他们的服务请求中提供特定的QoS首选项。因此,在用户的QoS偏好不确定的情况下,如何有效地向用户推荐服务是一个具有挑战性的问题。针对这一问题,本文针对用户需求的特点,提出了一种面向不确定QoS偏好的以多样化QoS为中心的服务推荐方法,该方法生成了具有期望QoS实现和多样性的服务列表。在一个真实的数据集上进行了大量的实验,以证明我们方法的有效性和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diversified QoS-Centric Service Recommendation for Uncertain QoS Preferences
With the wide adoption of SOA (Service Oriented Architecture), a massive amount of Web services emerge on the Internet. Finding the desired services becomes a challenge. Thus, service recommendation has become of paramount research to relieve users' difficulty in service selection. Existing Web service recommendation approaches employ utility functions or skyline techniques with the assumption that users can provide numerical QoS (Quality of Service) preferences. However, in practice, it is hard for users, even for professional users, to provide specific QoS preferences in their service requests. Thus, how to effectively recommend services to users when their QoS preferences are uncertain is a challenging issue. To solve the problem, this paper focuses on the characteristics of user requirements, and proposes a diversified QoS-centric service recommendation approach for uncertain QoS preferences, by which a list of services with desired QoS fulfillment and diversity are produced. Extensive experiments are conducted on a real-world dataset to demonstrate the effectiveness and efficiency of our approach.
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