Between context-aware media capture and multimedia content analysis - where do we find the promised land?

Various issues related to the multimedia information retrieval and media access are discussed. The feasible solutions for automatic signal-based analysis of media content are analyzed. The extent of user involvement in the content creation process is emphasized. The applications driving the creation and usage of context and metadata are also elaborated.

CARSA : A context-aware reasoning-based service agent model for AI planning of web service compostion

In order to achieve automatic and more intelligent service composition, dynamic description logic (DDL) is proposed and utilized as one emerging logic-level solution. However, reasoning optimization and utilization in such DDL-related solutions is still an open problem. In this paper, we propose the context-aware reasoning-based service agent model (CARSA) which exploits the relationships among different service consumers and providers, together with the corresponding optimization approach to strengthen the effectiveness of Web service composition. Through the model, two reasoning optimization methods are proposed based on the substitute relationship and the dependency relationship, respectively, so irrelevant actions can be filtered out of the reasoning space before the DDL reasoning process is carried out. The case study and experimental analysis demonstrates the capability of the proposed approach.

Context aware privacy in visual surveillance

In this paper we present preliminary work implementing dynamic privacy in public surveillance. The aim is to maximise the privacy of those under surveillance, while giving an observer access to sufficient information to perform their duties. As these aspects are in conflict, a dynamic approach to privacy is required to balance the system's purpose with the system's privacy. Dynamic privacy is achieved by accounting for the situation, or context, within the environment. The context is determined by a number of visual features that are combined and then used to determine an appropriate level of privacy.

Context-aware meta search engine for distributed web service

The ubiquity of the Internet and Web has led to the emergency of several Web search engines with varying capabilities. A weakness of existing search engines is the very extensive amount of hits that they can produce. Moreover, only a small number of web users actually know how to utilize the true power of Web search engines. Therefore, there is a need for searching infrastructure to help ease and guide the searching efforts of web users toward their desired objectives. In this paper, we propose a context-based meta-search engine and discuss its implementation on top of the actual Google.com search engine. The proposed meta-search engine benefits the user the most when the user does not know what exact document he or she is looking for. Comparison of the context-based meta-search engine with both Google and Guided Google shows that the results returned by context-based meta-search engine is much more intuitive and accurate than the results returned by both Google and Guided Google.

A graph-based model for context-aware recommendation using implicit feedback data

Recommender systems have been successfully dealing with the problem of information overload. However, most recommendation methods suit to the scenarios where explicit feedback, e.g. ratings, are available, but might not be suitable for the most common scenarios with only implicit feedback. In addition, most existing methods only focus on user and item dimensions and neglect any additional contextual information, such as time and location. In this paper, we propose a graph-based generic recommendation framework, which constructs a Multi-Layer Context Graph (MLCG) from implicit feedback data, and then performs ranking algorithms in MLCG for context-aware recommendation. Specifically, MLCG incorporates a variety of contextual information into a recommendation process and models the interactions between users and items. Moreover, based on MLCG, two novel ranking methods are developed: Context-aware Personalized Random Walk (CPRW) captures user preferences and current situations, and Semantic Path-based Random Walk (SPRW) incorporates semantics of paths in MLCG into random walk model for recommendation. The experiments on two real-world datasets demonstrate the effectiveness of our approach.

HorusCML: context-aware domain-specific visual languages designer

The objective behind building domain-specific visual languages (DSVLs) is to provide users with the most appropriate concepts and notations that best fit with their domain and experience. However, the existing DSVL designers do not support integrating environment and user context information when modeling, editing or viewing DSVL models at different locations, permissions, devices, etc. In this paper, we introduce HorusCML, a context-aware DSVL designer, which supports DSVL experts in integrating necessary context details within their DSVLs. The resultant DSVLs can reflect different facets, layouts, and behaviours according to context it is used in. We show a case study on developing a context-aware data flow diagram DSVL tool using HorusCML.

Exploring the effectiveness of true abnormal data elimination in context-aware web services recommendation

Recent years have witnessed a growing interest in context-aware recommender system (CARS), which explores the impact of context factors on personalized Web services recommendation. Basically, the general idea of CARS methods is to mine historical service invocation records through the process of context-aware similarity computation. It is observed that traditional similarity mining process would very likely generate relatively big deviations of QoS values, due to the dynamic change of contexts. As a consequence, including a considerable amount of deviated QoS values in the similarity calculation would probably result in a poor accuracy for predicting unknown QoS values. In allusion to this problem, this paper first distinguishes two definitions of Abnormal Data and True Abnormal Data, the latter of which should be eliminated. Second, we propose a novel CASR-TADE method by incorporating the effectiveness of True Abnormal Data Elimination into context-aware Web services recommendation. Finally, the experimental evaluations on a real-world Web services dataset show that the proposed CASR-TADE method significantly outperforms other existing approaches.

Diaspora, return and migrant architectures

Nearly all discourses on migration (to my knowledge) emphasise that the migrant is not so much a traveller, but a figure oriented towards settlement and a particular destination. Discourses on migration have attended more to the process and site of ‘arrival’, and few studies have focused on the process and site of ‘departure’. However, central to the thesis of this paper would be the testimony of two migrant houses – one in the city of  immigration (Melbourne, Australia), and the other in the village of emigration (Zavoj in Macedonia). The focus will be on the Zavoj house as a significant house, a house that points to a thesis about how architecture makes explicit other processes of migration, namely that of ‘return’. Here there are several intertwined communities and nations, and also different notions of community and nation. It has been noted that ‘diaspora’ is constituted through longer distances, severe separation, and a taboo on return. And yet implicit in many more ‘autobiographical’ accounts is that one only leaves with a promise to return. The conflict and question of ‘return’ is at the centre of the migrant’s imaginary. A study of the two houses of migration implicates a set of networks, forces, relations, circumscribing a much larger global geopolitical and cultural field that questions our understandings of diaspora, the currency of transnationalism, the binary structure of dwelling/travelling, and the fabric and fabrication of community. But the study goes inwards and underneath as well through the figure of the migrant, the figure through which the two migrant houses are deeply associated. The paper will explore the subjective nature of the thesis, the idea of a ‘migrant house’ as an imaginary architecture, a psychic geography, an imaginary community and sense of nationhood.

Technographic research in online education : context, culture and ICT consumption

Technologically-mediated learning environments are an increasingly common component of university experience. In this paper, the authors consider how the interrelated domains of policy contexts, new learning cultures and the consumption of information and communication technologies might be explored using the concept of technography. Understood here as a term referring to “the apprehension, reception, use, deployment, depiction and representation of technologies” (Woolgar, 2005, pp. 27-28), we consider how technographic studies in education might engage in productive dialogues with interdisciplinary research from the fields of cultural and cyber studies. We argue that what takes place in online learning and teaching environments is shaped by the logics and practices of technologies and their role in the production of new consumer cultures.