scholarly journals Rule-based solution for context-aware reasoning on mobile devices

2014 ◽  
Vol 11 (1) ◽  
pp. 171-193 ◽  
Author(s):  
Grzegorz Nalepa ◽  
Szymon Bobek

With the rapid evolution of mobile devices, the concept of context aware applications has gained a remarkable popularity in recent years. Smartphones and tablets are equipped with a variety of sensors including accelerometers, gyroscopes, and GPS, pressure gauges, light and GPS sensors. Additionally, the devices become computationally powerful which allows real-time processing of data gathered by their sensors. Universal network access viaWiFi hot-spots and GSM network makes mobile devices perfect platforms for ubiquitous computing. Most of existing frameworks for context-aware systems, are usually dedicated to static, centralized, clientserver architectures. However, mobile platforms require from the context modeling language and inference engine to be simple and lightweight. The model should also be powerful enough to allow not only solving simple context identification tasks but more complex reasoning. The original contribution of the paper is a proposal of a new rule-based context reasoning platform tailored to the needs of such intelligent distributed mobile computing devices. It contains a proposal of a learning middleware supporting context acquisition. The platform design is based on a critical review and evaluation of existing solutions given in this paper. A preliminary evaluation of the platform is given along with use cases including a social system supporting crime detection and investigation.

2013 ◽  
Vol 347-350 ◽  
pp. 2304-2310 ◽  
Author(s):  
Nan Xu ◽  
Wei Shi Zhang ◽  
Hua Dong Yang ◽  
Xiu Guo Zhang ◽  
Xing Xing

In this paper, we present a general and extensible context-aware computing ontology (CACOnt) for modeling context and providing inference mechanisms. CACOnt provides not only the generic context ontologies for capturing basic concepts about context, but also the extensibility for adding domain-specific ontologies in a hierarchical manner. CACOnt facilitates the context reasoning capabilities by providing semantic logics which is possible to combine with rule-based systems. However, the set of rules cannot entirely cover the domain of contexts, we present a semantic similarity-based rule matching algorithm as the solution to this problem.


Author(s):  
Prajit Kumar Das ◽  
Dibyajyoti Ghosh ◽  
Pramod Jagtap ◽  
Anupam Joshi ◽  
Tim Finin

Contemporary smartphones are capable of generating and transmitting large amounts of data about their users. Recent advances in collaborative context modeling combined with a lack of adequate permission model for handling dynamic context sharing on mobile platforms have led to the emergence of a new class of mobile applications that can access and share embedded sensor and context data. Most of the time such data is used for providing tailored services to the user but it can lead to serious breaches of privacy. We use Semantic Web technologies to create a rich notion of context. We also discuss challenges for context aware mobile platforms and present approaches to manage data flow on these devices using semantically rich fine-grained context-based policies that allow users to define their privacy and security need using tools we provide.


Author(s):  
Nan Jing ◽  
Yong Yao ◽  
Yanbo Ru

Context-aware advertising is one of the most critical components in the Internet ecosystem today because most WWW publisher’s revenue highly depends on the relevance of the displayed advertisement to the context of the user interaction. Existing research works in context-aware advertising mainly focus on analyzing either the content of the web page (in which it is also called contextual advertising), or the keywords of the user search. However, we have identified the limitations of these works when being extended into mobile web, which has become a major platform for users to access Internet with thanks to the new lightweight web technologies and the development of mobile devices. These mobile devices are equipped with networking capabilities and sensors that provide versatile contexts including physical environment, user internal and social community. These contexts, which are far beyond just page content and search keywords, should be well organized and utilized for online advertising to gain better user experience and reaction. In this chapter, we point out the aforementioned limitations of the existing works in context-aware advertising when being applied for mobile platforms. We also discuss the characteristics of the contexts that are available on mobile devices and clearly describe the challenges of utilizing these contexts to optimize the advertisement on mobile platforms. We then present a context-aware advertising framework that collects and integrates the user contexts to select, generate, and present advertising content. The purpose of this framework is to provide the mobile users with targeted and purposeful advertisement. Finally, we discuss the implementation aspects and one specific application of this framework and outline our future plans.


Author(s):  
Prajit Kumar Das ◽  
Dibyajyoti Ghosh ◽  
Pramod Jagtap ◽  
Anupam Joshi ◽  
Tim Finin

Contemporary smartphones are capable of generating and transmitting large amounts of data about their users. Recent advances in collaborative context modeling combined with a lack of adequate permission model for handling dynamic context sharing on mobile platforms have led to the emergence of a new class of mobile applications that can access and share embedded sensor and context data. Most of the time such data is used for providing tailored services to the user but it can lead to serious breaches of privacy. We use Semantic Web technologies to create a rich notion of context. We also discuss challenges for context aware mobile platforms and present approaches to manage data flow on these devices using semantically rich fine-grained context-based policies that allow users to define their privacy and security need using tools we provide.


2011 ◽  
Vol 2 (3) ◽  
pp. 38-52
Author(s):  
Nan Jing ◽  
Yong Yao ◽  
Yanbo Ru

Context-aware advertising is one of the most critical components in the Internet ecosystem today because most WWW publisher revenue highly depends on the relevance of the displayed advertisement to the context of the user interaction. Existing research work focuses on analyzing either the content of the web page or the keywords of the user search. However, there are limitations of these works when being extended into mobile computing domain, where mobile devices can provide versatile contexts, such as locations, weather, device capability, and user activities. These contexts should be well categorized and utilized for online advertising to gain better user experience and reaction. This paper examines the aforementioned limitations of the existing works in context-aware advertising when being applied for mobile platforms. A mobile advertising system is proposed, using location tracking and context awareness to provide targeted and meaningful advertisement to the customers on mobile devices. The three main modules of this comprehensive mobile advertising system are discussed, including advisement selection, advertisement presentation, and user context databases. A software prototype that is developed to conduct the case studies and validate this approach is presented.


Author(s):  
Abayomi Moradeyo Otebolaku ◽  
Maria Teresa Andrade

Audiovisual content consumption on mobile platforms is rising exponentially, and this trend will continue in the next years as mobile devices become more sophisticated. Thus, smartphones are gradually replacing our desktops as they increasingly become cheaper and more powerful with excellent multimedia processing support. As mobile users go about their routines, they continuously browse the web, seeking interesting content to consume, and also uploading personal content. However, users encounter huge volume of content that does not match their preferences, resulting in mobile information overload. Context-aware media personalization (CAMP) was proposed as a solution to this problem. CAMP assists users to select relevant content among alternatives considering users' preferences and contexts. This solution, however, are limited to static contexts. The contribution is mobile context-aware media personalization (MobCAMP), which is a special kind of personalization that utilizes users' contexts and activities to suggest media content according to the user's tastes and contextual situations.


Author(s):  
Prajit Kumar Das ◽  
Dibyajyoti Ghosh ◽  
Pramod Jagtap ◽  
Anupam Joshi ◽  
Tim Finin

Contemporary smartphones are capable of generating and transmitting large amounts of data about their users. Recent advances in collaborative context modeling combined with a lack of adequate permission model for handling dynamic context sharing on mobile platforms have led to the emergence of a new class of mobile applications that can access and share embedded sensor and context data. Most of the time such data is used for providing tailored services to the user but it can lead to serious breaches of privacy. We use Semantic Web technologies to create a rich notion of context. We also discuss challenges for context aware mobile platforms and present approaches to manage data flow on these devices using semantically rich fine-grained context-based policies that allow users to define their privacy and security need using tools we provide.


Author(s):  
Abayomi Moradeyo Otebolaku ◽  
Maria Teresa Andrade

Audiovisual content consumption on mobile platforms is rising exponentially and this trend will continue in the next years as mobile devices become more sophisticated. Thus, smartphones are gradually replacing our desktops as they increasingly become cheaper and more powerful with excellent multimedia processing support. As mobile users go about their routines, they continuously browse the Web, seeking interesting content to consume, and also uploading personal content. However, users encounter huge volume of content, that does not match their preferences, resulting in mobile information overload. Context-aware media personalization (CAMP) was proposed as a solution to this problem. CAMP assists users to select relevant content among alternatives considering users' preferences and contexts. This solution, however, are limited to static contexts. Our contribution is Mobile Context-Aware Media Personalization(MobCAMP), which is a special kind of personalization that utilizes user's contexts and activities to suggest media content according to the user's tastes and contextual situations.


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