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An approach to support the construction of adaptive Web applications

机译:一种支持建设自适应Web应用的方法

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Purpose - This paper aims to presents Real-time Usage Mining (RUM), an approach that exploits the rich information provided by client logs to support the construction of adaptive Web applications. The main goal of RUM is to provide useful information about the behavior of users that are currently browsing a Web application. By consuming this information, the application is able to adapt its user interface in real-time to enhance the user experience. RUM provides two types of services as follows: support for the detection of struggling users; and user profiling based on the detection of behavior patterns.Design/methodology/approach - RUM leverages the previous study on usability evaluation to provide a service that evaluates the usability of tasks performed by users while they browse applications. This evaluation is based on a metric that allows the detection of struggling users, making it possible to identify these users as soon as few logs from their interaction are processed. RUM also exploits log mining techniques to detect usage patterns, which are then associated with user profiles previously defined by the application specialist. After associating usage patterns to user profiles, RUM is able to classify users as they browse applications, allowing the application developer to tailor the user interface according to the users' needs and preferences.Findings - The proposed approach was exploited to improve user experience in real-world Web applications. Experiments showed that RUM was effective to provide support for struggling users to complete tasks. Moreover, it was also effective to detect usage patterns and associate them with user profiles. Originality/value - Although the literature reports studies that explore client logs to support both the detection of struggling users and the user profiling based on usage patterns, no existing solutions provide support for detecting users from specific profiles or struggling users, in real-time, while they are browsing Web applications. RUM also provides a toolkit that allows the approach to be easily deployed in any Web application.
机译:目的 - 本文旨在提出实时使用挖掘(朗姆酒),一种利用客户端日志提供的丰富信息的方法,以支持建设自适应Web应用程序。 RUM的主要目标是提供有关当前浏览Web应用程序的用户行为的有用信息。通过消耗此信息,应用程序能够实时调整其用户界面以增强用户体验。 RUM提供两种类型的服务,如下所示:支持检测努力用户;基于行为模式的检测,用户分析.Design/Methodology/Approach - Rum利用以前的可用性评估研究提供了一个服务,以提供评估用户在浏览应用程序的情况下执行的任务的可用性的服务。此评估基于允许检测努力用户的度量,从而可以在处理它们的交互的日志时立即识别这些用户。 RUM还利用日志挖掘技术来检测使用模式,然后与应用专家先前定义的用户配置文件相关联。在将使用模式与用户配置文件关联之后,RUM能够根据用户的需求和首选项来对用户进行分类用户,允许应用程序开发人员根据用户的需求和首选项来定制用户界面.Findings - 采用所提出的方法来提高真实的用户体验-world Web应用程序。实验表明,RUM是有效的,为努力提供努力完成任务,提供支持。此外,它也有效地检测使用模式并将它们与用户配置文件相关联。原创性/值 - 尽管探索客户日志的文献报告研究,以支持努力用户的检测和基于使用模式的用户分析,但没有现有的解决方案提供了支持从特定配置文件或努力的用户实时努力,当他们正在浏览Web应用程序时。 RUM还提供了一个工具包,允许在任何Web应用程序中轻松部署方法。

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