Detecting real user tasks by training on laboratory contextual attention metadata

Detecting the current task of a user is essential for providing her with contextualized and personalized support, and using Contextual Attention Metadata (CAM) can help doing so. Some recent approaches propose to perform automatic user task detection by means of task classifiers using such metadata. In this paper, we show that good results can be achieved by training such classifiers offline on CAM gathered in laboratory settings. We also isolate a combination of metadata features that present a significantly better discriminative power than classical ones

Exploiting the user interaction context for automatic task detection

Detecting the task a user is performing on her computer desktop is important for providing her with contextualized and personalized support. Some recent approaches propose to perform automatic user task detection by means of classifiers using captured user context data. In this paper we improve on that by using an ontology-based user interaction context model that can be automatically populated by (i) capturing simple user interaction events on the computer desktop and (ii) applying rule-based and information extraction mechanisms. We present evaluation results from a large user study we have carried out in a knowledge-intensive business environment, showing that our ontology-based approach provides new contextual features yielding good task detection performance. We also argue that good results can be achieved by training task classifiers `online' on user context data gathered in laboratory settings. Finally, we isolate a combination of contextual features that present a significantly better discriminative power than classical ones

Multifaceted Faculty Network Design and Management: Practice and Experience Report

We report on our experience on multidimensional aspects of our faculty's network design and management, including some unique aspects such as campus-wide VLANs and ghosting, security and monitoring, switching and routing, and others. We outline a historical perspective on certain research, design, and development decisions and discuss the network topology, its scalability, and management in detail; the services our network provides, and its evolution. We overview the security aspects of the management as well as data management and automation and the use of the data by other members of the IT group in the faculty.Comment: 19 pages, 11 figures, TOC and index; a short version presented at C3S2E'11; v6: more proofreading, index, TOC, reference

Automatic detection of accommodation steps as an indicator of knowledge maturing

Jointly working on shared digital artifacts – such as wikis – is a well-tried method of developing knowledge collectively within a group or organization. Our assumption is that such knowledge maturing is an accommodation process that can be measured by taking the writing process itself into account. This paper describes the development of a tool that detects accommodation automatically with the help of machine learning algorithms. We applied a software framework for task detection to the automatic identification of accommodation processes within a wiki. To set up the learning algorithms and test its performance, we conducted an empirical study, in which participants had to contribute to a wiki and, at the same time, identify their own tasks. Two domain experts evaluated the participants’ micro-tasks with regard to accommodation. We then applied an ontology-based task detection approach that identified accommodation with a rate of 79.12%. The potential use of our tool for measuring knowledge maturing online is discussed

CyberGuarder: a virtualization security assurance architecture for green cloud computing

Cloud Computing, Green Computing, Virtualization, Virtual Security Appliance, Security Isolation

EyeScout: Active Eye Tracking for Position and Movement Independent Gaze Interaction with Large Public Displays

While gaze holds a lot of promise for hands-free interaction with public displays, remote eye trackers with their confined tracking box restrict users to a single stationary position in front of the display. We present EyeScout, an active eye tracking system that combines an eye tracker mounted on a rail system with a computational method to automatically detect and align the tracker with the user's lateral movement. EyeScout addresses key limitations of current gaze-enabled large public displays by offering two novel gaze-interaction modes for a single user: In "Walk then Interact" the user can walk up to an arbitrary position in front of the display and interact, while in "Walk and Interact" the user can interact even while on the move. We report on a user study that shows that EyeScout is well perceived by users, extends a public display's sweet spot into a sweet line, and reduces gaze interaction kick-off time to 3.5 seconds -- a 62% improvement over state of the art solutions. We discuss sample applications that demonstrate how EyeScout can enable position and movement-independent gaze interaction with large public displays

Ambient Gestures

We present Ambient Gestures, a novel gesture-based system designed to support ubiquitous ‘in the environment’ interactions with everyday computing technology. Hand gestures and audio feedback allow users to control computer applications without reliance on a graphical user interface, and without having to switch from the context of a non-computer task to the context of the computer. The Ambient Gestures system is composed of a vision recognition software application, a set of gestures to be processed by a scripting application and a navigation and selection application that is controlled by the gestures. This system allows us to explore gestures as the primary means of interaction within a multimodal, multimedia environment. In this paper we describe the Ambient Gestures system, define the gestures and the interactions that can be achieved in this environment and present a formative study of the system. We conclude with a discussion of our findings and future applications of Ambient Gestures in ubiquitous computing