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Using Ontological Reasoning for an Adaptive E-Commerce Experience

机译:使用本体推理获得自适应电子商务体验

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As e-commerce applications proliferates the Web, the authors are often overwhelmed by the task of sifting through the copious volumes of information. Since the nature of foraging for information in such digital spaces can be characterized as the interaction between internal task representation and the external problem domain, the authors look at how expert systems can be used to reduce complexity of the task. They describe a conceptual framework to analyze user interactions based on mental representations. They also detail an expert system implementation using the ontology language OWL to express the semantics of the representations and the rule language SWRL to define the rule base for contextual reasoning. The chapter illustrates how an expert system can be used to guide users in an e-commerce setting by orchestrating a cognitive fit between the task environment and the task solution.
机译:随着电子商务应用程序在Web上的泛滥,作者经常不知所措,无法浏览大量信息。由于在这样的数字空间中搜寻信息的性质可以被描述为内部任务表示和外部问题域之间的交互,因此作者研究了如何使用专家系统来减少任务的复杂性。他们描述了一个基于心理表征来分析用户交互的概念框架。他们还详细介绍了使用本体语言OWL表示表示形式的语义和使用规则语言SWRL定义用于上下文推理的规则库的专家系统实现。本章说明了如何通过协调任务环境和任务解决方案之间的认知契合度,使用专家系统来指导电子商务环境中的用户。

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