Download Discovery Science: 18th International Conference, DS 2015, by Nathalie Japkowicz, Stan Matwin PDF

By Nathalie Japkowicz, Stan Matwin

This e-book constitutes the court cases of the seventeenth overseas convention on Discovery technological know-how, DS 2015, held in banff, AB, Canada in October 2015. The sixteen lengthy and 12 brief papers presendted including four invited talks during this quantity have been rigorously reviewed and chosen from forty four submissions.

The blend of contemporary advances within the improvement and research of equipment for locating scienti c wisdom, coming from computer studying, info mining, and clever facts research, in addition to their program in a variety of scienti c domain names, at the one hand, with the algorithmic advances in computer studying conception, nevertheless, makes each example of this joint occasion distinctive and engaging.

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Additional resources for Discovery Science: 18th International Conference, DS 2015, Banff, AB, Canada, October 4–6, 2015, Proceedings

Sample text

The In Vitro Fertilization (IVF) data set has been introduced in (Sokolova and Bobicev 2013). The data consists of 80 annotated discussions (1321 posts) gathered from the IVF Ages 35+ sub-forum2. Each post was annotated by two raters using three sentiment categories: ‘confusion’, ‘encouragement’ and ‘gratitude’, and one ‘factual’ category, a category transitional between ‘factual’ and ‘encouragement’ was named ‘endorsement’. Each post was assigned with one of the labels: ‘confusion’ (117 posts), ‘encouragement’ (310 posts), ‘gratitude’ (124 posts), ‘factual’ (433), ‘endorsement’ (162 posts), and 176 ‘ambiguous’ posts on which annotators disagreed.

For this alternative approach, we require a way of scoring the quality of a behaviour model based on the results of a simulation run or runs. Conveniently, in three recent studies, Puckett, Kelley, and Ouellette have described in detail the movement of individual midges (Chironomus riparius) in a swarm [6, 9, 10]. We suggest specific criteria that allow us to assess the fidelity of the model to nature, based on this quantitative data and separate qualitative observations of midge behaviour [4, 7].

These systems are rather sensitive to their parameters, requiring careful tweaking in order to perform well. In a further paper, H¨ ohn et al. [10] specifically raise this as an area for improvement: their experiments work well, but do not necessarily generalise to a large variety of maps. The system of Mello et al. was developed for a large set of rather homogeneous maps, which means that it was merited to spend significant effort to find good parameter values. In contrast, we aim to handle diverse maps, each with relatively small user effort.

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