Semi-automated dialogue act classification for situated social agents in games

As a step toward simulating dynamic dialogue between agents and humans in virtual environments, we describe learning a model of social behavior composed of interleaved utterances and physical actions. In our model, utterances are abstracted as {speech act, propositional content, referent} triples. After training a classifier on 100 gameplay logs from The Restaurant Game annotated with dialogue act triples, we have automatically classified utterances in an additional 5,000 logs. A quantitative evaluation of statistical models learned from the gameplay logs demonstrates that semi-automatically classified dialogue acts yield significantly more predictive power than automatically clustered utterances, and serve as a better common currency for modeling interleaved actions and utterances

Validating the detection of everyday concepts in visual lifelogs

The Microsoft SenseCam is a small lightweight wearable camera used to passively capture photos and other sensor readings from a user's day-to-day activities. It can capture up to 3,000 images per day, equating to almost 1 million images per year. It is used to aid memory by creating a personal multimedia lifelog, or visual recording of the wearer's life. However the sheer volume of image data captured within a visual lifelog creates a number of challenges, particularly for locating relevant content. Within this work, we explore the applicability of semantic concept detection, a method often used within video retrieval, on the novel domain of visual lifelogs. A concept detector models the correspondence between low-level visual features and high-level semantic concepts (such as indoors, outdoors, people, buildings, etc.) using supervised machine learning. By doing so it determines the probability of a concept's presence. We apply detection of 27 everyday semantic concepts on a lifelog collection composed of 257,518 SenseCam images from 5 users. The results were then evaluated on a subset of 95,907 images, to determine the precision for detection of each semantic concept and to draw some interesting inferences on the lifestyles of those 5 users. We additionally present future applications of concept detection within the domain of lifelogging. © 2008 Springer Berlin Heidelberg

Inter-rater reliability of the EPUAP pressure ulcer classification system using photographs

Background. Many classification systems for grading pressure ulcers are discussed in the literature. Correct identification and classification of a pressure ulcer is important for accurate reporting of the magnitude of the problem, and for timely prevention. The reliability of pressure ulcer classification systems has rarely been tested. Aims and objectives. The purpose of this paper is to examine the inter-rater reliability of classifying pressure ulcers according to the European Pressure Ulcer Advisory Panel classification system when using pressure ulcer photographs.Design. Survey was among pressure ulcer experts.Methods. Fifty-six photographs were presented to 44 pressure ulcer experts. The experts classified the lesions as normal skin, blanchable erythema, pressure ulcer (four grades) or incontinence lesion. Inter-rater reliability was calculated.Results. The multirater-Kappa for the entire group of experts was 0.80 (P < 0.001).Various groups of experts obtained comparable results. Differences in classifications are mainly limited to 1 degree of difference. Incontinence lesions are most often confused with grade 2 (blisters) and grade 3 pressure ulcers (superficial pressure ulcers).Conclusions. The inter-rater reliability of the European Pressure Ulcer Advisory Panel classification appears to be good for the assessment of photographs by experts. The difference between an incontinence lesion and a blister or a superficial pressure ulcer does not always seem clear.Relevance to clinical practice. The ability to determine correctly whether a lesion is a pressure ulcer lesion is important to assess the effectiveness of preventive measures. In addition, the ability to make a correct distinction between pressure ulcers and incontinence lesions is important as they require different preventive measures. A faulty classification leads to mistaken measures and negative results. Photographs can be used as a practice instrument to learn to discern pressure ulcers from incontinence lesions and to get to know the different grades of pressure ulcers. The Pressure Ulcer Classification software package has been developed to facilitate learning