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AUTOMATIC GENERATION OF USER MODEL FROM NON-TRIVIAL HYPERMEDIA IN ADAPTIVE E-LEARNING HYPERMEDIA SYSTEM

机译:自适应电子学习超媒体系统中非平凡超媒体用户模型的自动生成

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Adaptive E-learning Hypermedia System keeps characteristics of particular students and adapts its output in accord to them. Such characteristic can be level of student's knowledge of particular information domain, prerequisite knowledge needed to understand particular information, specific preferences and needs of student (for example the disabled) and many others. There are several adaptation techniques (adaptive features), which define adaptive behavior of system. Student's characteristic is stored in user model. In general, there are two main parts of user model: general information, which is valid for all hypermedia documents in adaptive hypermedia systems and particular information relevant only to particular hypermedia document. The second part of model can be automatically generated from hypermedia topology and used adaptation techniques (this part of model is only the secondary information). Such automated generation can improve data consistency and stability of adaptive E-learning hypermedia system. This paper deals with formal description of problem, propose algorithm for automated user model generation based on formal description and discuss consequences in adaptive system implementation.
机译:自适应电子学习超媒体系统保留特定学生的特征,并根据他们的需求调整其输出。这样的特征可以是学生对特定信息领域的知识水平,理解特定信息所需的先决知识,学生(例如残疾人)的特定偏好和需求等。有几种自适应技术(自适应功能),它们定义了系统的自适应行为。学生的特征存储在用户模型中。通常,用户模型有两个主要部分:通用信息,对自适应超媒体系统中的所有超媒体文档均有效;以及仅与特定超媒体文档相关的特定信息。模型的第二部分可以从超媒体拓扑结构和使用的自适应技术中自动生成(模型的这一部分仅是辅助信息)。这种自动生成可以提高自适应电子学习超媒体系统的数据一致性和稳定性。本文处理问题的形式化描述,提出基于形式化描述的自动用户模型生成算法,并讨论在自适应系统实现中的后果。

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