Novel Applications Integrate Location and Context Information

Strobbe, Matthias; Laere, Olivier Van; Ongenae, Femke; Dauwe, Samuel; Dhoedt, Bart; Turck, Filip De; Demeester, Piet; Luyten, Kris

doi:10.1109/mprv.2011.60

Cited by 18 publications

(4 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The self-learning extension of the oNCS is visualized in Figure 3. The oNCS was built as an extension of the Context-Aware Service Platform (CASP) [13], which consists of a collection of OSGi [14] The Learning Pipeline is implemented using the Pipes-and-Filters architectural design pattern [18]. A pipeline consists of a set of filters, implementing small processing steps, which are connected by pipes.…”

Section: Self-learning Extension Of the Oncsmentioning

confidence: 99%

A self-learning nurse call system

Ongenae

Claeys

Kerckhove

et al. 2014

Computers in Biology and Medicine

Self Cite

View full text Add to dashboard Cite

The complexity of continuous care settings has increased due to an ageing population, a dwindling number of caregivers and increasing costs. Electronic healthcare (eHealth) solutions are often introduced to deal with these issues.This technological equipment further increases the complexity of healthcare as the caregivers are responsible for integrating and configuring these solutions to their needs. Small differences in user requirements often occur between various environments where the services are deployed. It is difficult to capture these nuances at development time. Consequently, the services are not tuned towards the users' needs. This paper describes our experiences with extending an eHealth application with self-learning components such that it can automatically adjust its parameters at run-time to the users' needs and preferences. These components gather information about the usage of the application. This collected * Corresponding author: Tel.: +32 9 331 49 38, Fax: +32 9 331 48 99 information is processed by data mining techniques to learn the parameter values for the application. Each discovered parameter is associated with a probability, which expresses its reliability. Unreliable values are filtered. The remaining parameters and their reliability are integrated into the application.The eHealth application used is the ontology-based Nurse Call System (oNCS), which assesses the priority of a call based on the current context and assigns the most appropriate caregiver to a call. Decision trees and Bayesian networks are used to learn and adjust the parameters of the oNCS. For a realistic dataset of 1,050 instances, correct parameter values are discovered very efficiently as the components require at most 100 milliseconds execution time and 20 megabyte memory.

show abstract

Section: Self-learning Extension Of the Oncsmentioning

confidence: 99%

A self-learning nurse call system

Ongenae

Claeys

Kerckhove

et al. 2014

Computers in Biology and Medicine

Self Cite

View full text Add to dashboard Cite

show abstract

“…Location models and sensors such as Global Positioning System (GPS) and Wi-Fi that capture geometric information of objects that are humanreadable have been proposed by various researchers. Location context in recommender systems is often acquired or sensed implicitly through GPS or Wi-Fi location sensors in mobile devices [13]. Other recommender systems which require the exact location information usually rely on explicit approaches such as [14].…”

Section: Contextual Information Sensingmentioning

confidence: 99%

Socially-Aware Venue Recommendation for Conference Participants

Xia

Asabere

Rodrigues

et al. 2013

2013 IEEE 10th International Conference on Ubiquitous Intelligence and Computing and 2013 IEEE 10th International Conference On

View full text Add to dashboard Cite

Abstract-Current research environments are witnessing high enormities of presentations occurring in different sessions at academic conferences. This situation makes it difficult for researchers (especially juniors) to attend the right presentation session(s) for effective collaboration. In this paper, we propose an innovative venue recommendation algorithm to enhance smart conference participation. Our proposed algorithm, Social Aware Recommendation of Venues and Environments (SARVE), computes the Pearson Correlation and social characteristic information of conference participants. SARVE further incorporates the current context of both the smart conference community and participants in order to model a recommendation process using distributed community detection. Through the integration of the above computations and techniques, we are able to recommend presentation sessions of active participant presenters that may be of high interest to a particular participant. We evaluate SARVE using a real world dataset. Our experimental results demonstrate that SARVE outperforms other state-of-the-art methods.

show abstract

“…The design and development of context-aware solutions [1][2][3][4] aim to align information and services with the needs of users as well as the characteristics of mobile devices and underlying networks. The significance of context-aware solutions can be realised through a wide range of applications in different areas such as personalization of services, marketing, advertisement, healthcare, traffic management, and dynamic configuration of computing devices and networks.…”

Section: Introductionmentioning

confidence: 99%

Every Cloud Has a Push Data Lining: Incorporating Cloud Services in a Context-Aware Application

Grønli

Hansen

Ghinea

et al. 2015

Mobile Information Systems

View full text Add to dashboard Cite

We investigated context-awareness by utilising multiple sources of context in a mobile device setting. In our experiment we developed a system consisting of a mobile client, running on the Android platform, integrated with a cloud-based service. These components were integrated using push messaging technology. One of the key features was the automatic adaptation of smartphones in accordance with implicit user needs. The novelty of our approach consists in the use of multiple sources of context input to the system, which included the use of calendar data and web based user configuration tool, as well as that of an external, cloud-based, configuration file storing user interface preferences which, pushed at log-on time irrespective of access device, frees the user from having to manually configure its interface. The system was evaluated via two rounds of user evaluations (n= 50 users), the feedback of which was generally positive and demonstrated the viability of using cloud-based services to provide an enhanced context-aware user experience.

show abstract

Novel Applications Integrate Location and Context Information

Cited by 18 publications

References 9 publications

A self-learning nurse call system

A self-learning nurse call system

Socially-Aware Venue Recommendation for Conference Participants

Every Cloud Has a Push Data Lining: Incorporating Cloud Services in a Context-Aware Application

Contact Info

Product

Resources

About