User context and personalisation

The importance of user context as a means of delivering personalised and context-sensitive systems is discussed. Relevant aspects of personalisation and context technology are covered. The intention is to inspire those interested in Case-base reasoning and personalisation from background and experience in other disciplines such as information retrieval, adaptive user interfaces, user modelling and mobile computing. Descriptions of personalisation and context are followed by their use in information retrieval and their importance and use in ambient computing. Relevant literature that may be a motivating source for interested readers are provided. Various questions are also raised in initiating discussion on this topic

MLContext: A Context-Modeling Language for Context-Aware Systems

Context awareness refers to systems that can both sense and react based on their environment. The complexity of these systems makes necessary to apply software engineering techniques in their development, such as Model-Driven Software development (MDD). One of the main difficulties that developers of context-aware systems must tackle is how to manage the needed context information. In this paper, we present MLContext, a textual Domain Specific Language (DSL) which is specially tailored for modeling context information and automatically generating software artefacts from context models. It has been designed to provide a high-level abstraction, to be an easy to learn, and to promote reuse of context models. We have built a toolkit including an editor and a parser to convert MLContext textual specifications into models. As a proof of concept, we have automatically generated ontologies and Java code for the OCP middleware. MLContext models can be reused in applications with the same context because they do not include details related to the platforms or the implementation. These context models can be specified by non-developers users because MLContext provides high-level abstractions of the domain

Moving towards personalising translation technology

Technology has had an important impact on the work of translators and represents a shift in the boundaries of translation work over time. Improvements in machine translation have brought about further boundary shifts in some translation work and are likely to continue having an impact. Yet translators sometimes feel frustrated with the tools they use. This chapter looks to the field of personalisation in information technology and proposes that personalising translation technology may be a way of improving translator-computer interaction. Personalisation of translation technology is considered from the perspectives of context, user modelling, trust, motivation and well-being

Design Principles for Personalized Assistance Systems that Respect Privacy

Personalized assistance systems (PAS) provide real-time assistance tailored to individual users to improve efficiency in the workplace. PAS communicate dynamically with users through wearable computing devices. To deliver such personalized assistance, PAS need personal data from the individuals who wear them. However, concerns over data protection and security can negatively influence the extent to which users accept personalized assistance systems. The key aspects in this regard that the literature currently lacks include data protection law and the employee perspective. Hence, we develop seven design principles for PAS that respect user privacy through employee-determined approaches to data collection and use. We developed the principles based on a systematic literature review, user personas, privacy control, and European Union legal requirements for privacy by design and privacy by default. Our design principles, which we evaluated in a focus group and an expert workshop, provide a framework to help practitioners and software developers mitigate adoption barriers due to privacy concerns. Our study also contributes to the theoretical discussion of current developments in personalized assistance in the workplace by providing a new perspective on ensuring employees accept the required data collection and use

Event and map content personalisation in a mobile and context-aware environment.

Effective methods for information access are of the greatest importance for our modern lives “ particularly with respect to handheld devices. Personalisation is one such method which models a users characteristics to deliver content more focused to the users needs. The emerging area of sophisticated mobile computing devices has started to inspire new forms of personalised systems that include aspects of the persons contextual environment. This thesis seeks to understand the role of personalisation and context, to evaluate the effectiveness of context for content personalisation and to investigate the event and map content domain for mobile usage. The work presented in this thesis has three parts: The first part is a user experiment on context that investigated the contextual attributes of time, location and interest, with respect to participants perception of their usefulness. Results show highly dynamic and interconnected effects of context on participants usefulness ratings. In the second part, these results were applied to create a predictive model of context that was related to attribution theory and then combined with an information retrieval score to create a weighted personalisation model. In the third part of this work, the personalisation model was applied in a mobile experiment. Participants solved situational search tasks using a (i) non-personalized and a (ii) personalized mobile information system, and rating entertainment events based on usefulness. Results showed that the personalised system delivered about 20% more useful content to the mobile user than the non-personalised system, with some indication for reduced search effort in terms of time and the amount of queries per task. The work presented provides evidence for the promising potential of context to facilitate personalised information delivery to users of mobile devices. Overall, it serves as an example of an investigation into the effectiveness of context from multiple angles and provides a potential link to some of the aspects of psychology as a potential source for a deeper understanding of contextual processes in humans

A Knowledge-driven Distributed Architecture for Context-Aware Systems

As the number of devices increases, it becomes a challenge for the users to use them effectively. This is more challenging when the majority of these devices are mobile. The users and their devices enter and leave different environments where different settings and computing needs may be required. To effectively use these devices in such environments means to constantly be aware of their whereabouts, functionalities and desirable working conditions. This is impractical and hence it is imperative to increase seamless interactions between the users and devices,and to make these devices less intrusive. To address these problems, various responsive computing systems, called context- aware systems, have been developed. These systems rely on architectures to perceive their physical environments in order to appropriately and effortlessly respond. Currently, the majority of the existing architectures focus on acquiring data from sensors, interpreting and sharing it with these systems