Challenges in Annotation of useR Data for UbiquitOUs Systems: Results from the 1st ARDUOUS Workshop (original) (raw)
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Labelling user data is a central part of the design and evaluation of pervasive systems that aim to support the user through situation-aware reasoning. It is essential both in designing and training the system to recognise and reason about the situation, either through the definition of a suitable situation model in knowledge-driven applications [28, 3], or through the preparation of training data for learning tasks in data-driven models [19]. Hence, the quality of annotations can have a significant impact on the performance of the derived systems. Labelling is also vital for validating and quantifying the performance of applications. In particular, comparative evaluations require the production of benchmark datasets based on high-quality and consistent annotations. With pervasive systems relying increasingly on large datasets for designing and testing models of users’ activities, the process of data labelling is becoming a major concern for the community [1]. Labelling is a manual ...
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Abstract Context and context-awareness have been central issues in ubiquitous computing research for the last decade. Advances with regard to context acquisition and activity recognition allow interesting small scale applications. However in larger systems including many sensors and actuators and spanning multiple administrative domains are still remain as unsolved central issues. Particularly, in the areas of reasoning and context-fusion there are many open questions.
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Ubiquitous display environments are public places with various situated public displays. These displays are intended to provide relevant information to people in their vicinity, where this may include the regular inhabitants of the space as well as visitors. For this latter group, it is particularly challenging to provide relevant information. This is because personalization relies on the availability of information about the individual (or group). Ubiquitous user modeling research tries to address this challenge.
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ABSTRACT With regard to deploying context-aware applications, there has been a steadily increasing interest in context representation for efficient description of complex situations in daily life. However, most ways of describing context are specific to purpose of each service or give undue value to particular information, eg location. In this paper, we propose unified context, which describes usercentric situation without dependence on purpose of any service, in terms of 5W1H (Who, What, Where, When, How, and Why).