69,789 research outputs found

    Natural Language Generation enhances human decision-making with uncertain information

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    Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. We present a comparison of different information presentations for uncertain data and, for the first time, measure their effects on human decision-making. We show that the use of Natural Language Generation (NLG) improves decision-making under uncertainty, compared to state-of-the-art graphical-based representation methods. In a task-based study with 442 adults, we found that presentations using NLG lead to 24% better decision-making on average than the graphical presentations, and to 44% better decision-making when NLG is combined with graphics. We also show that women achieve significantly better results when presented with NLG output (an 87% increase on average compared to graphical presentations).Comment: 54th annual meeting of the Association for Computational Linguistics (ACL), Berlin 201

    Weather and Climate Information for Tourism

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    The tourism sector is one of the largest and fastest growing global industries and is a significant contributor to national and local economies around the world. The interface between climate and tourism is multifaceted and complex, as climate represents both a vital resource to be exploited and an important limiting factor that poses risks to be managed by the tourism industry and tourists alike. All tourism destinations and operators are climate-sensitive to a degree and climate is a key influence on travel planning and the travel experience. This chapter provides a synopsis of the capacities and needs for climate services in the tourism sector, including current and emerging applications of climate services by diverse tourism end-users, and a discussion of key knowledge gaps, research and capacity-building needs and partnerships that are required to accelerate the application of climate information to manage risks to climate variability and facilitate successful adaptation to climate change

    Short interval control for the cost estimate baseline of novel high value manufacturing products – a complexity based approach

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    Novel high value manufacturing products by default lack the minimum a priori data needed for forecasting cost variance over of time using regression based techniques. Forecasts which attempt to achieve this therefore suffer from significant variance which in turn places significant strain on budgetary assumptions and financial planning. The authors argue that for novel high value manufacturing products short interval control through continuous revision is necessary until the context of the baseline estimate stabilises sufficiently for extending the time intervals for revision. Case study data from the United States Department of Defence Scheduled Annual Summary Reports (1986-2013) is used to exemplify the approach. In this respect it must be remembered that the context of a baseline cost estimate is subject to a large number of assumptions regarding future plausible scenarios, the probability of such scenarios, and various requirements related to such. These assumptions change over time and the degree of their change is indicated by the extent that cost variance follows a forecast propagation curve that has been defined in advance. The presented approach determines the stability of this context by calculating the effort required to identify a propagation pattern for cost variance using the principles of Kolmogorov complexity. Only when that effort remains stable over a sufficient period of time can the revision periods for the cost estimate baseline be changed from continuous to discrete time intervals. The practical implication of the presented approach for novel high value manufacturing products is that attention is shifted from the bottom up or parametric estimation activity to the continuous management of the context for that cost estimate itself. This in turn enables a faster and more sustainable stabilisation of the estimating context which then creates the conditions for reducing cost estimate uncertainty in an actionable and timely manner

    Weather and Climate Information for Tourism

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    The tourism sector is one of the largest and fastest growing global industries and is a significant contributor to national and local economies around the world. The interface between climate and tourism is multifaceted and complex, as climate represents both a vital resource to be exploited and an important limiting factor that poses risks to be managed by the tourism industry and tourists alike. All tourism destinations and operators are climate-sensitive to a degree and climate is a key influence on travel planning and the travel experience. This chapter provides a synopsis of the capacities and needs for climate services in the tourism sector, including current and emerging applications of climate services by diverse tourism end-users, and a discussion of key knowledge gaps, research and capacity-building needs and partnerships that are required to accelerate the application of climate information to manage risks to climate variability and facilitate successful adaptation to climate change
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