scholarly journals Enhancing Existing Communication Services with Context Awareness

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Bachir Chihani ◽  
Emmanuel Bertin ◽  
Irsalina Salsabila Suprapto ◽  
Julien Zimmermann ◽  
Noël Crespi

Context aware communication services rely on information sources and sensors, to derive users’ current situation and potential needs, and to adapt their communication services accordingly. If extensive studies have been driven on context awareness by industrials and researchers from academia, the design of such systems without modifying uses and manners of underlying communication services—while keeping them simple, intuitive, and reactive—remains a challenge. In this work, we introduce a context aware communication system that takes into account user’s preferences, workload, and situation to customize telephony services. In this implementation, we use IMS for communication management. The benefits of this implementation are the enhancement of IMS with context awareness features, and the coupling of user preferences with contextual information to provide improved service customization, without modifying the user experience.

2011 ◽  
pp. 1040-1050
Author(s):  
James M. Laffey ◽  
Christopher J. Amelung

Context-aware activity notification systems have potential to improve and support the social experience of online learning. The authors of this chapter have developed a Context-aware Activity Notification System (CANS) that monitors online learning activities and represents relevant contextual information by providing notification and making the learning activity salient to other participants. The chapter describes previous efforts to develop and support online learning context awareness systems; it also defines the critical components and features of such a system. It is argued that notification systems can provide methods for using the context of activity to support members’ understanding of the meaning of activity. When designed and implemented effectively, CANS can turn course management systems (CMS) into technologies of social interaction to support the social requirements of learning.


Author(s):  
M. Fahim Ferdous Khan ◽  
Ken Sakamura

Context-awareness is a quintessential feature of ubiquitous computing. Contextual information not only facilitates improved applications, but can also become significant security parameters – which in turn can potentially ensure service delivery not to anyone anytime anywhere, but to the right person at the right time and place. Specially, in determining access control to resources, contextual information can play an important role. Access control models, as studied in traditional computing security, however, have no notion of context-awareness; and the recent works in the nascent field of context-aware access control predominantly focus on spatio-temporal contexts, disregarding a host of other pertinent contexts. In this paper, with a view to exploring the relationship of access control and context-awareness in ubiquitous computing, the authors propose a comprehensive context-aware access control model for ubiquitous healthcare services. They explain the design, implementation and evaluation of the proposed model in detail. They chose healthcare as a representative application domain because healthcare systems pose an array of non-trivial context-sensitive access control requirements, many of which are directly or indirectly applicable to other context-aware ubiquitous computing applications.


2009 ◽  
pp. 56-64
Author(s):  
Jun Sun ◽  
Marshall Scott Poole

Advances in wireless network and multimedia technologies enable mobile commerce (m-commerce) information service providers to know the location and surroundings of mobile consumers through GPS-enabled and camera-embedded cell phones. Context awareness has great potential for creating new service modes and improving service quality in m-commerce. To develop and implement successful context-aware applications in m-commerce, it is critical to understand the concept of the “context” of mobile consumers and how to access and utilize contextual information in an appropriate way. This article dissects the context construct along both the behavioral and physical dimensions from the perspective of mobile consumers, developing a classification scheme for various types of consumer contexts. Based on this classification scheme, it discusses three types of context-aware applications—noninteractive mode, interactive mode and community mode—and describes newly proposed applications as examples of each.


Author(s):  
Jun Sun ◽  
Marshall Scott Poole

Advances in wireless network and multimedia technologies enable mobile commerce (m-commerce) information service providers to know the location and surroundings of mobile consumers through GPS-enabled and camera-embedded cell phones. Context awareness has great potential for creating new service modes and improving service quality in m-commerce. To develop and implement successful context-aware applications in m-commerce, it is critical to understand the concept of the “context” of mobile consumers and how to access and utilize contextual information in an appropriate way. This article dissects the context construct along both the behavioral and physical dimensions from the perspective of mobile consumers, developing a classification scheme for various types of consumer contexts. Based on this classification scheme, it discusses three types of context-aware applications—non-interactive mode, interactive mode and community mode—and describes newly proposed applications as examples of each.


2021 ◽  
Author(s):  
Qingbo Hao ◽  
Ke Zhu ◽  
Chundong Wang ◽  
Peng Wang ◽  
Xiuliang Mo ◽  
...  

Abstract The rapid development of Mobile Internet has spa-wned various mobile applications (apps). A large number of apps make it difficult for users to choose apps conveniently, causing the app overload problem. As the most effective tool to solve the problem of app overload, the app recommendation has attracted extensive attention of researchers. Traditional recommendation methods usually use historical data of apps used by users to explore their preferences, and then make an app recommendation list for users. Although the traditional app recommendation methods have achieved certain results, the performance of app recommendation still needs to be improved due to the following two reasons. On the one hand, it is difficult to construct traditional app recommendation models when facing with the sparse user-app interaction data. On the other hand, contextual information has a large impact on users’ app usage preferences, which is often overlooked by traditional app recommendation methods. To overcome the aforementioned problems, we proposed a Context-aware Feature Deep Interaction Learning (CFDIL) method to explore user preferences, and then perform app recommendation by learning potential user-app relationships in different contexts. The novelty of CFDIL is as follows: (1) CFDIL incorporates contextual features into users' preferences modeling by constructing a novel user and app feature portrait. (2) The problem of data sparsity is effectively solved by the use of dense user and app feature portraits, as well as the tensor operations for label sets. (3) CFDIL trains a new deep network structure, which can make accurate app recommendation using the contextual information and attribute information of users and apps. We applied CFDIL on three real datasets and conducted extensive experiments, which showed that CFDIL outperformed the benchmark method.


Author(s):  
Hafiz Amaad ◽  
Naveed Jhamat ◽  
Kashif Riaz ◽  
Zeeshan Arshad

The availability of huge volumes of online research papers over scholarly communities has been increasing rapidly with the evolution of the Internet. Meanwhile, several researchers confront troubles while retrieving suitable and relevant research papers according to their research necessities due to information overload. Besides, the research necessities vary from researcher to researcher according to their contextual state and the online behavior in sequential access. Conventional recommendation approaches for instance content-based filtering (CBF) and collaborative filtering (CF) utilize content features and rankings correspondingly, in order to produce recommendations for the researchers. In spite of this, it is inevitable to incorporate scholar’s contextual information and sequential access behavior into the recommendation procedure to generate accurate and personalized recommendations for research papers. Conventional recommender systems do not incorporate such information in the recommended procedure to compute similarities of scholars and provide recommendations; thus, they are more liable to produce an irrelevant list of recommendations in a scholarly environment. Moreover, conventional recommendation approaches generate inaccurate recommendations in presence of a high level of sparsity in the rankings. In this article, we introduce a novel method for research paper recommendations that incorporates the benefits of collective filtering (CF), context-awareness, and sequential pattern mining (SPM) to propose research papers to scholars in a hybrid manner. Context-awareness in our methodology involves the scholar's contextual state, such as skill level and research goals; SPM is used to mine weblogs and reveal sequential access actions of scholars, and CF is used to measure predictions based on correlations between scholars and generate context-aware and sequential trend mining based recommendations for the targeted scholars. Experimental evaluations of our approach indicate the excellence of our approach over other baseline approaches in terms of precision, recall, F1, and mean absolute error (MAE).


Author(s):  
Sara Saeedi ◽  
Xueyang Zou ◽  
Mariel Gonzales ◽  
Steve Liang

The ubiquity of mobile sensors (such as GPS, accelerometer and gyroscope) together with increasing computational power have enabled an easier access to contextual information, which proved its value in next generation of the recommender applications. The importance of contextual information has been recognized by researchers in many disciplines, such as ubiquitous and mobile computing, to filter the query results and provide recommendations based on different user status. A context-aware recommendation system (CoARS) provides a personalized service to each individual user, driven by his or her particular needs and interests at any location and anytime. Therefore, a contextual recommendation system changes in real time as a user’s circumstances changes. CoARS is one of the major applications that has been refined over the years due to the evolving geospatial techniques and big data management practices. In this paper, a CoARS is designed and implemented to combine the context information from smartphones’ sensors and user preferences to improve efficiency and usability of the recommendation. The proposed approach combines user’s context information (such as location, time, and transportation mode), personalized preferences (using individuals past behavior), and item-based recommendations (such as item’s ranking and type) to personally filter the item list. The context-aware methodology is based on preprocessing and filtering of raw data, context extraction and context reasoning. This study examined the application of such a system in recommending a suitable restaurant using both web-based and android platforms. The implemented system uses CoARS techniques to provide beneficial and accurate recommendations to the users. The capabilities of the system is evaluated successfully with recommendation experiment and usability test.


Author(s):  
M. Fahim Ferdous Khan ◽  
Ken Sakamura

Context-awareness is a quintessential feature of ubiquitous computing. Contextual information not only facilitates improved applications, but can also become significant security parameters – which in turn can potentially ensure service delivery not to anyone anytime anywhere, but to the right person at the right time and place. Specially, in determining access control to resources, contextual information can play an important role. Access control models, as studied in traditional computing security, however, have no notion of context-awareness; and the recent works in the nascent field of context-aware access control predominantly focus on spatio-temporal contexts, disregarding a host of other pertinent contexts. In this paper, with a view to exploring the relationship of access control and context-awareness in ubiquitous computing, the authors propose a comprehensive context-aware access control model for ubiquitous healthcare services. They explain the design, implementation and evaluation of the proposed model in detail. They chose healthcare as a representative application domain because healthcare systems pose an array of non-trivial context-sensitive access control requirements, many of which are directly or indirectly applicable to other context-aware ubiquitous computing applications.


2010 ◽  
pp. 885-895 ◽  
Author(s):  
James M. Laffey ◽  
Christopher J. Amelung

Context-aware activity notification systems have potential to improve and support the social experience of online learning. The authors of this chapter have developed a context-aware activity notification system (CANS) that monitors online learning activities and represents relevant contextual information by providing notification and making the learning activity salient to other participants. The chapter describes previous efforts to develop and support online learning context awareness systems; it also defines the critical components and features of such a system. It is argued that notification systems can provide methods for using the context of activity to support members’ understanding of the meaning of activity. When designed and implemented effectively, CANS can turn course management systems (CMS) into technologies of social interaction to support the social requirements of learning.


Author(s):  
Amina HAMEURLAINE ◽  
Samiha Brahimi

This chapter is consecrated to provide background information that encompass the basic concepts of context-aware pervasive computing systems. The major challenges that researchers need to consider when conducting research in context-aware pervasive computing systems and the most interesting approaches that can be used in order to deal with these challenges are reviewed. This chapter describes also the basic design principles of context-aware pervasive systems and depicts different models for representing and reasoning upon contextual information and an overview of the most known development frameworks of context-aware systems and application adaptation is presented too. Moreover, this chapter describes the usefulness of using context-awareness in ubiquitous healthcare domain and the major challenges in using context-awareness in this domain. The well-known works that have been proposed in the field of Ubiquitous healthcare are discussed too.


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