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Context Recognition: Towards Automatic Query Generation

机译:上下文识别:走向自动查询生成

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In this paper, we present an ontology-based approach in designing knowledge model for context recognition (CR) systems. The main focus in this paper is on the use of an ontology to facilitate the generation of user-based queries to the CR system. By leveraging from the ontology, users need not know about sensor details and the structure of the ontology in expressing queries related to events of interest. To validate the approach and demonstrate the flexibility of the ontology for query generation, the ontology has been integrated in two separate application domains. The first domain considers a health care system implemented for the GiraffPlus project where the query generation process is automated to request information about activities of daily living. The second application uses the same ontology for an air quality monitoring application in the home. Since these two systems are independently developed for different purposes, the ease of applying the ontology upon them can be considered as a credit for its generality.
机译:在本文中,我们提出了一种用于设计上下文识别(CR)系统知识模型的基于本体的方法。本文的主要重点是使用本体来促进对CR系统的基于用户的查询的生成。通过利用本体,用户在表达与感兴趣事件有关的查询时不需要了解传感器的详细信息和本体的结构。为了验证该方法并证明本体用于查询生成的灵活性,已将本体集成在两个单独的应用程序域中。第一个域考虑为GiraffPlus项目实施的医疗保健系统,在该系统中,查询生成过程会自动进行,以请求有关日常生活活动的信息。第二个应用程序将相同的本体用于家庭中的空气质量监测应用程序。由于这两个系统是为不同目的而独立开发的,因此将本体应用于它们的简便性可以认为是其普遍性的功劳。

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