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Context information brings new opportunities for efficient and effective applications and services on mobile devices. A wide range of research has exploited context dependency, i.e. the relations between context(s) and the outcome, to achieve significant, quantified, performance gains for a variety of applications and services. These works typically have to deal with the challenges of multiple context...
The number of applications available since the late 2010's, and the number of smartphone user sharply increasing. However, not all applications are not useful or helpful. In other words, to obtain satisfactory results in the search can be difficult means. Users to find what they want to search for a many times. To solve this problem, previous studies have proposed the use of recommender systems. Most...
Community Context-attribute-centric Collaborative Information Environment (CCCIE) enables provision of services to users with same interests, by employing time awareness and demand-oriented perspective to transform one to one (1-1), one dimensional location based service paradigm to one to many (1-N), n-dimensional situation-aware community services. Unlike conventional Location Based Services (LBS)...
As devices are expected to be aware of their environment, the challenge becomes how to accommodate these abilities with the power constraints which plague modern mobile devices. We present a framework for an embedded approach to context recognition which reduces power consumption. This is accomplished by identifying class-sensor dependencies, and using prediction methods to identify likely future...
Context-aware self-adaptive applications monitor and exploit knowledge about external operating conditions and adapt to changes in the execution context. Modern smartphones are equipped with several sensors, like GPS sensor or accelerometer. Additionally, context reasoners and external context providers exist. Thus, it is possible that several context providers offer information of the same type (e...
Applying Web service in mobile peer-to-peer service provisioning enhances the interoperability and resolves the heterogeneous challenges of ubiquitous environments. However, due to the nature of mobile peer-to-peer environments, a central repository for assisting service discovery is nonexistent, service discovery process relies on routing techniques, which increase the latency of the service interaction...
In this paper, an acoustic and visual signal based context awareness system is proposed for a mobile application. The proposed system senses and determines, in real time, user contextual information, such as where the user is or what the user does, by processing signals from the microphone and the camera embedded in the mobile device. An initial implementation of the algorithms into a smart phone...
High level context recognition and situation detection are enabling technologies for unobtrusive mobile computing systems. Significant progress has been made in processing and managing context information, leading to sophisticated frameworks, middlewares, and algorithms. Despite great improvements, context aware systems still require a significantly increased recognition accuracy for high-level context...
Location based social networking (LBSN) applications are part of a new suite of emerging social networking tools that run on the Web 2.0 platform. LBSN is the convergence between location based services (LBS) and online social networking (OSN). LBSN applications offer users the ability to look up the location of another “friend” remotely using a smart phone, desktop or other device, anytime and anywhere...
In this paper, we target the problem of the situation-aware application (task) recommendation on mobile devices. To tackle this problem, we develop both supervised and unsupervised approaches. We use Naive Bayesian as a supervised approach, and co-clustering and vector quantization (VQ) as unsupervised approaches. We evaluate the performance of the proposed approaches with both synthetic and actual...
This paper presents a semantic and adaptive service for context-aware information management system for supporting ubiquitous computing applications in a smart vehicle space. In ubiquitous computing environments, systems consisting of different device types, operating systems, network interfaces, and communication protocols. These contexts change dynamically and the applications have to adapt their...
Auditory contexts are recognized from mixtures of sounds from mobile userspsila everyday environments. We describe our implementation of auditory context recognition for mobile devices. In our system we use a set of support vector machine classifiers to implement the recognizer. Moreover, static and runtime resource consumption of the system are measured and reported.
In our daily life we frequently use mobile devices to interact with the people and things on the Internet. However, finding the right things when needed is getting difficult and frustrating. In this paper, we introduce a relatively new problem of non-collaborative personal interest mining using contexts and ratings available for items of interest. We present multi-step algorithms to extract personal...
The evaluation of a mobile application must be done considering its purpose and contexts on which it is suppose to be used. In this paper we introduce a multimodal artefact manipulation tool and discuss the results of its evaluation: conducted with a sub-set of its final users, in real contexts, considering: different interaction modalities (voice recognition, gesture recognition, direct interaction,...
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