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Semantic client-side approach for web personalization of SaaS-based cloud services

机译:基于SaaS的云服务的Web个性化的语义客户端方法

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The demand of software as a service (SaaS)-based services delivering computing resources as on-demandrnsoftware is on the rise in the IT industry. However, one of the drawbacks of the existing SaaS services is thatrnthey offer limited or no personalization of the services provided according to the users profile. Personalizationrnas mentioned in the literature has been a key driver in the adoption and usage of various applications andrnin providing better service experience to the users. However, overwhelming majority of such personalizedrnservices rely extensively on the server side, without embracing fast-developing client-side technologies. InrnSaaS-based cloud services, utilizing this technology is necessary considering their limited processing specifications.rnApproaches have been proposed in the literature that focus on cloud-based personalization usingrnclient-side technologies but none of them actually address all the different components that are required for arnscalable and holistic personalization framework for SaaS-based cloud services. In this paper, we address thisrndrawback by proposing a user-focussed personalization framework. Our proposed framework takes advantagernof powerful client side browsers to reduce server overheads, ameliorate performance, establish highrnintelligence and enrich data processing. To validate and demonstrate the applicability of our framework, wernbuild a prototype model and compare its performance against existing approaches using different metrics.
机译:在IT行业中,基于软件即服务(SaaS)的服务以点播软件的形式提供计算资源的需求正在上升。但是,现有SaaS服务的缺点之一是,根据用户配置文件,它们只能提供有限的个性化服务,或者无法提供个性化服务。文献中提到的Personalizationrnas一直是各种应用程序的采用和使用的主要驱动力,并且为用户提供了更好的服务体验。但是,绝大多数此类个性化服务在很大程度上不依赖于服务器端,而没有采用快速发展的客户端技术。考虑到基于InrnSaaS的云服务的有限处理规范,必须使用这种技术。rn文献中已经提出了一些方法,这些方法侧重于使用rnr客户端技术进行基于云的个性化,但是它们都没有真正解决可伸缩性所需的所有不同组件。基于SaaS的云服务的整体个性化框架。在本文中,我们通过提出以用户为中心的个性化框架来解决这种缺点。我们提出的框架利用功能强大的客户端浏览器来减少服务器开销,改善性能,建立高级智能并丰富数据处理。为了验证和证明我们框架的适用性,我们构建了一个原型模型,并使用不同的指标将其性能与现有方法进行了比较。

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