An Ontology for Mobile Device Sensor-Based Context Awareness

Korpipää, Panu; Mäntyjärvi, Jani

doi:10.1007/3-540-44958-2_37

Cited by 77 publications

(54 citation statements)

References 6 publications

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“…To develop flexible and efficient context ontologies that cover the wide range of possible contexts is a challenging task. The most important goals when designing a context ontology include [20]:…”

Section: Context Modelsmentioning

confidence: 99%

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A survey on context-aware systems

Baldauf

Dustdar

Rosenberg

2007

IJAHUC

1,550

810

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Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context data and adapting sysAbstract. Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context data and adapting systems' behavior accordingly. Especially in combination with mobile devices such mechanisms are of great value and claim to increase usability tremendously. In this paper, we present a layered architectural framework for context-aware systems. Based on our suggested framework for analysis, we introduce various existing context-aware systems focusing on context-aware middleware and frameworks, which ease the development of context-aware applications. We discuss various approaches and analyze important aspects in context-aware computing on the basis of the presented systems.

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Section: Context Modelsmentioning

confidence: 99%

“…the Resource Description Language (RDF) [19,20,21] and the Web Ontology Language OWL [22,32,34,35]. A single context atom can be described with a couple of attributes.…”

Section: Context Modelsmentioning

confidence: 99%

A survey on context-aware systems

Baldauf

Dustdar

Rosenberg

2007

IJAHUC

1,550

810

View full text Add to dashboard Cite

show abstract

“…For example, Yusheng et al [8] proposed the ComSensor method to compose data of several sensors for context with more semantics. Korpipää and Mäntyjärvi [9] developed an ontology of the constituents of context derived from mobile sensors such that context instances can be easily derived facilitating the development of context-aware mobile applications. The ContextTorrent [10] is an Android-based framework that processes raw context into semantically searchable context by modeling context as an ontology.…”

Section: Related Workmentioning

confidence: 99%

Context Management for Supporting Context-aware Android Applications Development

Elazhary

Althubyani

Ahmed

et al. 2017

Int. J. Interact. Mob. Technol.

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Abstract-Building context-aware mobile applications is one of the most ambitious areas of research. Such applications can change their behavior according to context or perform specific tasks in specific contexts. Regardless of the application, all context-aware mobile applications share the need to retrieve and process context information. This paper presents a Context Management tool for the Android platform (ACM). ACM allows easy access to internal onboard mobile sensors and hardware features extracting corresponding raw data. Raw context is processed into higher-level more human-readable context that is provided seamlessly to the mobile applications. Different methods are used for this purpose including fuzzy classifiers. Since different mobiles have different sensors and hardware features, ACM can adapt to the mobile device by deactivating access to unavailable ones. Information regarding the available sensors and hardware features and their specifications can also be queried. Additionally, applications can request notifications regarding context change or specific context values. In addition to providing developers with supporting classes and methods, ACM is accompanied by an application that allows developers to examine its functionality and capabilities before using it. The application can be also used to examine the readings of the different sensors in different situations and thus calibrate them as needed. Additionally, it can be used to modify and personalize default interpretations of raw context values to high-level ones. ACM has been tested empirically and the results show extreme interest of context-aware mobile application developers in its promising capabilities and that it is conducive to facilitating, speeding up and triggering development of many more of such applications.

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“…It is not lightweight and does not reuse other vocabularies. Korpipää et al [14] present a context model designed for mobile, contextaware applications. It is general, but does not reuse existing terms and it is not extensible.…”

Section: A Context Representationmentioning

confidence: 99%

An Ontology-based Contextual Pre-filtering Technique for Recommender Systems

Karpus

Vagliano

Goczyła

et al. 2016

Annals of Computer Science and Information Systems

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Abstract-Context-aware Recommender Systems aim to provide users with the most adequate recommendations for their current situation. However, an exact context obtained from a user could be too specific and may not have enough data for accurate rating prediction. This is known as the data sparsity problem. Moreover, often user preference representation depends on the domain or the specific recommendation approach used. Therefore, a big effort is required to change the method used. In this paper we present a new approach for contextual pre-filtering (i.e. using the current context to select a relevant subset of data). Our approach can be used with existing recommendation algorithms. It is based on two ontologies: Recommender System Context ontology, which represents the context, and Contextual Ontological User Profile ontology, which represents user preferences. We evaluated our approach through an offline study which showed that when used with well-known recommendation algorithms it can significantly improve the accuracy of prediction.

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An Ontology for Mobile Device Sensor-Based Context Awareness

Cited by 77 publications

References 6 publications

A survey on context-aware systems

A survey on context-aware systems

Context Management for Supporting Context-aware Android Applications Development

An Ontology-based Contextual Pre-filtering Technique for Recommender Systems

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