Context Model and Context Acquisition for Ubiquitous Content Access in ULearning Environments

Yang, Stephen J. H.; Huang, Adam; Chen, Rick; Tseng, Shian‐Shyong; Shen, Yen-Shih

doi:10.1109/sutc.2006.47

Cited by 36 publications

(18 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…• U-Learn 3 [48]: this ontology-based context-model is focused on the support of learning. The learner and the learning content are described by two ontologies (learner ontology and content metadata) and a rulebased system provides a content-to-learner matching mechanism.…”

Section: The Context Modelsmentioning

confidence: 99%

A data-oriented survey of context models

et al. 2007

View full text Add to dashboard Cite

Context-aware systems are pervading everyday life, therefore context modeling is becoming a relevant issue and an expanding research field. This survey has the goal to provide a comprehensive evaluation framework, allowing application designers to compare context models with respect to a given target application; in particular we stress the analysis of those features which are relevant for the problem of data tailoring. The contribution of this paper is twofold: a general analysis framework for context models and an upto-date comparison of the most interesting, data-oriented approaches available in the literature.

show abstract

Section: The Context Modelsmentioning

confidence: 99%

A data-oriented survey of context models

et al. 2007

View full text Add to dashboard Cite

show abstract

“…In this system, context includes all the entities, their roles, the relations between the entities and the situations of the entities. In [12], Yang et al, describe an ontology based context model which is specific to learning environments.…”

Section: B Context-aware or Integration Frameworkmentioning

confidence: 99%

Contextual information integration platform for humanitarian relief

Krishnamoorthy

Agrawala

2011

Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief

View full text Add to dashboard Cite

Abstract-It is well recognized that context plays a significant role in all human endeavors. All decisions are based on information which has to be interpreted in context. By making the information systems context-aware we can have systems that significantly improve the human capabilities to handle situations context. In this paper, we highlight the significance of Context that wireless devices should be able to support, especially in the event of a calamity or a disaster to provide much more effective support to the relief efforts. In such situations, where wireless device users need to be provided with critical information for purposes such as evacuation, relief work etc., it is equally important to provide information that suits current situation of the user while taking into account the current environment around the user. We present Rover 2.0, framework for contextual information integration for wireless devices. With our belief that information processing systems should only provide support to the human decision maker (and not attempt to replace him/her), the Rover provides means for supporting the flow of information filtered and augmented using relevant contextual information. Our framework uses a paradigm for handling context information that includes user specific context combined with activity context and common context. We outline the significance of context-awareness with the help of a mobile application/system developed at Maryland on how effective such systems can be in situations of disaster or calamity.

show abstract

“…8 The aim of this work is to show the way context can be used to define contextaware data views over large information systems, tailoring only the data that are relevant to a given application use-case to obtain a personalized subset of the available information. The use of context over the data has been introduced in references 1,6,10,12 but it is far from being explored in depth. With respect to the above classification, these systems add a new perspective that we can call datatailoring-oriented since they aim at the reduction of the size of data by means of contextual preferences.…”

Section: Community-basedmentioning

confidence: 99%