Annotation evolution: how Web 2.0 technologies are enabling a change in annotation practice

Are Web 2.0 tools and technologies changing how and why scholars annotate their research sources? We begin to answer this question by assessing current technology and tools that support new functions for one of the most common scholarly research activity: taking notes. The results suggest a new approach to personalized information retrieval.published or submitted for publicationis peer reviewe

Teaching Categories to Human Learners with Visual Explanations

We study the problem of computer-assisted teaching with explanations. Conventional approaches for machine teaching typically only provide feedback at the instance level e.g., the category or label of the instance. However, it is intuitive that clear explanations from a knowledgeable teacher can significantly improve a student's ability to learn a new concept. To address these existing limitations, we propose a teaching framework that provides interpretable explanations as feedback and models how the learner incorporates this additional information. In the case of images, we show that we can automatically generate explanations that highlight the parts of the image that are responsible for the class label. Experiments on human learners illustrate that, on average, participants achieve better test set performance on challenging categorization tasks when taught with our interpretable approach compared to existing methods

Olfoto: designing a smell-based interaction

We present a study into the use of smell for searching digi-tal photo collections. Many people now have large photo libraries on their computers and effective search tools are needed. Smell has a strong link to memory and emotion so may be a good way to cue recall when searching. Our study compared text and smell based tagging. For the first stage we generated a set of smell and tag names from user de-scriptions of photos, participants then used these to tag pho-tos, returning two weeks later to answer questions on their photos. Results showed that participants could tag effec-tively with text labels, as this is a common and familiar task. Performance with smells was lower but participants performed significantly above chance, with some partici-pants using smells well. This suggests that smell has poten-tial. Results also showed that some smells were consistently identified and useful, but some were not and highlighted issues with smell delivery devices. We also discuss some practical issues of using smell for interaction

Ono: an open platform for social robotics

In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform