Context awareness

About: Context awareness is a research topic. Over the lifetime, 5790 publications have been published within this topic receiving 119944 citations.

A framework for contextual mediation in mobile and ubiquitous computing applied to the context-aware adaptation of maps

Abstract: Context has many aspects, which may vary widely, such as the device, environment and user. The perception of data in different contexts also varies widely. We present a new, flexible approach to meeting needs and limits arising from context: contextual mediation. In this paper limits are defined as goals over managed system resources. These can be met by the selection of data, taking into account preferences over its semantic and syntactic properties. The specification of this selection is presented in detail and the supporting framework is described. We illustrate our description with examples from a context-aware map application and present experimental results and experiences which demonstrate that contextual mediation enhances the usability of the application in restrictive contexts of use.

A formal proximity model for RBAC systems

Abstract: To combat the threat of information leakage through pervasive access, researchers have proposed several extensions to the popular role-based access control (RBAC) model. Such extensions can incorporate contextual features, such as location, into the policy decision in an attempt to restrict access to trustworthy settings. In many cases, though, such extensions fail to reflect the true threat, which is the presence or absence of other users, rather than absolute locations. For instance, for location-aware separation of duty, it is more important to ensure that two people are in the same room, rather than in a designated, pre-defined location. Prox-RBAC was proposed as an extension to consider the relative proximity of other users with the help of a pervasive monitoring infrastructure. However, that work offered only an informal view of proximity, and unnecessarily restricted the domain to spatial concerns. In this work, we present a more rigorous definition of proximity based on formal topological relations. In addition, we show that this definition can be applied to several additional domains, such as social networks, communication channels, attributes, and time; thus, our policy model and language is more flexible and powerful than the previous work. In addition to proposing the model, we present a number of theoretical results for such systems, including a complexity analysis, templates for cryptographic protocols, and proofs of security features.

Path2Go: Context-aware services for mobile real-time multimodal traveler information

Abstract: Mobile platforms are now becoming a more and more important medium for providing information to travelers on the move. To improve the accuracy and relevance of the mobile traveler information, context awareness has become a active research topic. In this paper, we describe algorithms and services provided by Path2Go, a multimodal traveler information system developed by California PATH, UC Berkeley. The Path2Go activity detection algorithm, the core of the context-aware design, has made the following contributions: (1) it uses a rule-based multi-hypothesis Bayesian method for mode detection, to address the limitations of using mobile phone GPS for activity detection and increase the speed of convergence; (2) it fuses GPS data from transit vehicles and the GPS of the user's mobile phone for better activity detection; and (3) it enables several experimental services, including variable-frequency client-server communication and need-based GPS use. Field testing of the Path2Go activity detection algorithms showed reasonably good results. The Path2Go application has also been made available to the public through iPhone, Android and Windows Mobile platforms, with some of the features discussed in this paper included.

Recommendation system for sharing economy based on multidimensional trust model

Abstract: The recommendation system are widely adopted in today's mainstream online sharing services, providing useful prediction of user's rating or user's preferences of sharing items (such as products, movies, books, and news articles). A key challenge of recommendation systems in sharing economy is to employ prediction algorithms to estimate the matching items with considering their interests and needs. The environment-context has been recognized as an important factor to consider in personalized recommender systems. Since dynamic information in environment-context describes the situation of items and users, the information affects the user's decision process essentially to apply in recommender systems. However, most model-based collaborative filtering approaches such as Matrix Factorization do not provide an easy way of integrating context information into the model. In this paper, we introduce a Multidimensional Trust model based on Tensor Factorization. The generalization of Matrix Factorization allows for a flexible and generic integration of contextual information. According to the different types of context, the Multidimensional Trust model considers the additional dimensions for the representation of the data as a tensor. This is achieved by going through the collecting user's behavior based on rating analysis and identification of users' historical activity and viewing patterns. The benefits behavior solutions, which use the handle intelligently to meet the users' needs, are the focus of this paper.

Exploiting Location and Contextual Information to Develop a Comprehensive Framework for Proactive Handover in Heterogeneous Environments

Abstract: The development and deployment of several wireless and cellular networks mean that users will demand to be always connected as they move around Mobile nodes will therefore have several interfaces and connections will be seamlessly switched among available networks using vertical handover techniques Proactive handover mechanisms can be combined with the deployment of a number of location-based systems that provide location information to a very high degree of accuracy in different contexts Furthermore, this new environment will also allow contextual information such as user profiles as well as the availability of using location and contextual information to provide efficient handover mechanisms Using location-based techniques, it is possible to demonstrate that the Time Before Vertical Handover as well as the Network Dwell Time can be accurately estimated These techniques are dependent on accurately estimating the handover radius This paper investigates how location and context awareness can be used to estimate the best handover radius The paper also explores how such techniques may be integrated into the Y-Comm architecture which is being used to explore the development of future mobile networks Finally, the paper highlights the use of ontological techniques as a mechanism for specifying and prototyping such systems