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Context awareness

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


Papers
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Journal ArticleDOI
TL;DR: This paper describes and evaluates a pre-filtering approach to context-aware recommendation, called distributional-semantics pre- Filtering (DSPF), which exploits in a novel way the distributional semantics of contextual conditions to build more precise context- aware rating prediction models.
Abstract: Context-aware recommender systems improve context-free recommenders by exploiting the knowledge of the contextual situation under which a user experienced and rated an item. They use data sets of contextually-tagged ratings to predict how the target user would evaluate (rate) an item in a given contextual situation, with the ultimate goal to recommend the items with the best estimated ratings. This paper describes and evaluates a pre-filtering approach to context-aware recommendation, called distributional-semantics pre-filtering (DSPF), which exploits in a novel way the distributional semantics of contextual conditions to build more precise context-aware rating prediction models. In DSPF, given a target contextual situation (of a target user), a matrix-factorization predictive model is built by using the ratings tagged with the contextual situations most similar to the target one. Then, this model is used to compute rating predictions and identify recommendations for that specific target contextual situation. In the proposed approach, the definition of the similarity of contextual situations is based on the distributional semantics of their composing conditions: situations are similar if they influence the user's ratings in a similar way. This notion of similarity has the advantage of being directly derived from the rating data; hence it does not require a context taxonomy. We analyze the effectiveness of DSPF varying the specific method used to compute the situation-to-situation similarity. We also show how DSPF can be further improved by using clustering techniques. Finally, we evaluate DSPF on several contextually-tagged data sets and demonstrate that it outperforms state-of-the-art context-aware approaches.

47 citations

Proceedings ArticleDOI
10 Apr 2011
TL;DR: An algorithm for a context-aware network selection is proposed that is based on a modified WPM for access network selection and a weight distribution method based on sensitivity analysis of WPM is used for the most influential criteria based on the state of user at a given time.
Abstract: Context-awareness is a key ingredient in any ubiquitous and pervasive system and provides intelligence to the system, allowing computing devices to make appropriate and timely decisions on behalf of users. One of the important aspects of mobility management is the dynamic selection of the best access network for a multimodal device when there is a need to perform a handover. Multi Attribute Decision Making (MADM) is one of the successfully used methods in the literature to solve decision making problems. The problem of access network selection has been addressed by decision making methods based on available network information. However, the quality of information is not considered. Weighted Product Method (WPM) is an MADM method that penalizes the unreliable attributes in making a decision. It does not suffer from ranking abnormalities and its cheaper computational cost makes it a suitable candidate for decision making in a dynamic situation. In this paper, an algorithm for a context-aware network selection is proposed that is based on a modified WPM for access network selection. We use a weight distribution method based on sensitivity analysis of WPM for the most influential criteria based on the state of user at a given time. Our evaluation is based on comparing WPM with TOPSIS that is successfully used in many decision making problems.

47 citations

Journal ArticleDOI
TL;DR: This paper investigates the state-of-the-art smart grid information subsystem, communication infrastructure and its emerging trends and potentials, called anSDN-enabled smart grid, and presents an abstract business model, candidate SDN applications and common architecture of the SDN- enabled smart grid.
Abstract: Context and situational awareness are key features and trends of the smart grid and enable adaptable, flexible and extendable smart grid services. However, the traditional hardware-dependent communication infrastructure is not designed to identify the flow and context of data, and it focuses only on packet forwarding using a pre-defined network configuration profile. Thus, the current network infrastructure may not dynamically adapt the various business models and services of the smart grid system. To solve this problem, software-defined networking (SDN) is being considered in the smart grid, but the design, architecture and system model need to be optimized for the smart grid environment. In this paper, we investigate the state-of-the-art smart grid information subsystem, communication infrastructure and its emerging trends and potentials, called an SDN-enabled smart grid. We present an abstract business model, candidate SDN applications and common architecture of the SDN-enabled smart grid. Further, we compare recent studies into the SDN-enabled smart grid depending on its service functionalities, and we describe further challenges of the SDN-enabled smart grid network infrastructure.

46 citations

Journal ArticleDOI
TL;DR: A smart mobile, self-configuring, context-aware architecture devised to enable the rapid prototyping of personal health monitoring applications for different scenarios, by exploiting commercial wearable sensors and mobile devices as well as knowledge-based technologies is presented.

46 citations

Journal Article
TL;DR: This paper proposes a formal model and notation for expressing context-aware computations and assumes a notion of context that is relative to the needs of each individual component, and expects context-awareness to be maintained in a totally transparent manner with minimal programming effort.
Abstract: Context-aware computing refers to a computing paradigm in which the behavior of individual components is determined by the circumstances in which they find themselves to an extent that greatly exceeds the typical system/environment interaction pattern common to most modern computing. The environment has an exceedingly powerful impact on a particular application component either because the latter needs to adapt in response to changing external conditions or because it relies on resources whose availability is subject to continuous change. In this paper we seek to develop a systematic understanding of the quintessential nature of context-aware computing by constructing a formal model and notation for expressing context-aware computations. We start with the basic premise that, in its most extreme form, context should be made manifest in a manner that is highly local in appearance and decoupled in fact. Furthermore, we assume a notion of context that is relative to the needs of each individual component, and we expect context-awareness to be maintained in a totally transparent manner with minimal programming effort. We construct the model from first principles, seek to root our decisions in these formative assumptions, and make every effort to preserve minimality of concepts and elegance of notation.

46 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20236
202227
2021105
2020184
2019224
2018258