Knowledgezoom for java: A concept-based exam study tool with a zoomable open student model

This paper presents our attempt to develop a personalized exam preparation tool for Java/OOP classes based on a fine-grained concept model of Java knowledge. Our goal was to explore two most popular student model-based approaches: open student modeling and problem sequencing. The result of our work is a Java exam preparation tool, Knowledge Zoom. The tool combines an open concept-level student model component, Knowledge Explorer and a concept-based sequencing component, Knowledge Maximizer into a single interface. This paper presents both components of Knowledge Zoom, reports results of its evaluation, and discusses lessons learned. © 2013 IEEE

Managing contextual information in semantically-driven temporal information systems

Context-aware (CA) systems have demonstrated the provision of a robust solution for personalized information delivery in the current content-rich and dynamic information age we live in. They allow software agents to autonomously interact with users by modeling the user’s environment (e.g. profile, location, relevant public information etc.) as dynamically-evolving and interoperable contexts. There is a flurry of research activities in a wide spectrum at context-aware research areas such as managing the user’s profile, context acquisition from external environments, context storage, context representation and interpretation, context service delivery and matching of context attributes to users‘ queries etc. We propose SDCAS, a Semantic-Driven Context Aware System that facilitates public services recommendation to users at temporal location. This paper focuses on information management and service recommendation using semantic technologies, taking into account the challenges of relationship complexity in temporal and contextual information

Sensory semantic user interfaces (SenSUI)

Rapid evolution of the World Wide Web with its underlying sources of data, knowledge, services and applications continually attempts to support a variety of users, with different backgrounds, requirements and capabilities. In such an environment, it is highly unlikely that a single user interface will prevail and be able to fulfill the requirements of each user adequately. Adaptive user interfaces are able to adapt information and application functionalities to the user context. In contrast, pervasive computing and sensor networks open new opportunities for context aware platforms, one that is able to improve user interface adaptation reacting to environmental and user sensors. Semantic web technologies and ontologies are able to capture sensor data and provide contextual information about the user, their actions, required applications and environment. This paper investigates the viability of an approach where semantic web technologies are used to maximize the efficacy of interface adaptation through the use of available ontology

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions

Context Aware Middleware Architectures: Survey and Challenges

Abstract: Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work