2 research outputs found

    Baran: a service-oriented cloud-based user monitoring and data analysis framework

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    Most humans now live in an age of connected digital devices where their interactions with these devices are recorded in a number of ways, by different organisations, under various levels of user control. A user is often unaware of how much data they create, of where the data resides, and of how their data is used. It is challenging for a user to inspect all this personal data, to control the storage and use of the data, and to exploit the data for their benefit in a safe way. These are the challenges that this thesis addresses. The focus is on the user’s digital trail of information – i.e. the record of user interactions and associated context information from the digital devices associated with the user. The digital devices associated with a user, and with which they interact, might include smartphones, laptops, smart watches, fitness bands, and smart household appliances. The thesis develops a conceptual model and extensible data structure, called the UDI (User Digital Imprint), which accommodates a variety of digital data from digital devices along with information derived from that data. A software framework, Baran, is developed that implements the UDI and provides services that support the gathering, management and analysis of the user data. The Baran framework allows the user to inspect and analyse their data and supports (under user control) the sharing of the data in order that assistive services for the user can be provided by 3rd parties. The framework is cloud-based and service-oriented, enabling the framework to make use of external services (e.g. machine learning services) and to provide services for external entities (e.g. supplying some subset of user data to a smart coffee maker). Thus, Baran can be extended with both user services and external services, where the sharing of user data with external entities is directly under user control on a per-use basis. By gathering, analysing and making available comprehensive information about a user’s digital interactions, Baran also enables study of aspects of User Experience (UX), as might be of interest to UX researchers or product designers. Three case studies are presented to demonstrate aspects of Baran and how it can be used in different scenarios. Rather than a limited-scope, specific solution (such as recent functionality introduced by Google and Apple) Baran provides a general extensible framework that covers a range of user digital interactions on a variety of devices, and enables a wide range of applications, where all data sharing is under explicit user control

    A pro-active and dynamic prediction assistance using BaranC framework

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    Monitoring user interaction activities provides the basis for creating a user model that can be used to predict user behaviour and enable user assistant services. The BaranC framework provides components that perform UI monitoring (and collect all associated context data), builds a user model, and supports services that make use of the user model. In this case study, a Next-App prediction service is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic; it is dynamic both in responding to the current context, and also in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service
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