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MASHA: A multi-agent system handling user and device adaptivity of Web sites

机译:MASHA:处理网站用户和设备适应性的多代理系统

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摘要

A user that navigates on the Web using different devices should be characterized by a global profile, which represents his behaviour when using all these devices. Then, the user's profile could be usefully exploited when interacting with a site agent that is able to provide useful recommendations on the basis of the user's interests, on one hand, and to adapt the site presentation to the device currently exploited by the user, on the other hand. However, it is not suitable to construct such a global profile by a software running on the exploited device since this device (e.g., a mobile phone or a palmtop) may have limited resources. Therefore, in this paper, we propose a multi-agent architecture, called MASHA, handling user and device adaptivity of Web sites, in which each device is provided with a client agent that autonomously collects information about the user's behaviour associated to just that device. However, the user profile contained in this client is continuously updated with information coming from a unique server agent, associated with the user. Such information is collected by the server agent from the different devices exploited by the user, and represents a global user profile. The third component of this architecture, called adapter agent, is capable to generate a personalized representation of the Web site, containing some useful recommendations derived by both an analysis of the user profile and the suggestions coming from other users exploiting the same device.
机译:使用不同设备在Web上浏览的用户应以全局配置文件为特征,该配置文件代表其在使用所有这些设备时的行为。然后,当与站点代理进行交互时,可以有效地利用用户的个人资料,该站点代理一方面能够基于用户的兴趣提供有用的建议,另一方面可以使站点的显示适应用户当前使用的设备。另一方面。但是,由于该设备(例如,移动电话或掌上电脑)的资源可能有限,因此不适合通过在被利用设备上运行的软件来构造这样的全局配置文件。因此,在本文中,我们提出了一种称为MASHA的多代理体系结构,用于处理网站的用户和设备适应性,其中为每个设备提供一个客户端代理,该客户端代理自动收集有关与该设备相关的用户行为的信息。但是,此客户端中包含的用户配置文件会使用来自与该用户相关联的唯一服务器代理的信息不断更新。这样的信息由服务器代理从用户利用的不同设备中收集,并代表全局用户配置文件。此体系结构的第三个组件称为适配器代理,它能够生成网站的个性化表示,其中包含一些有用的建议,这些建议是通过对用户配置文件的分析以及来自使用同一设备的其他用户的建议得出的。

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