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Titlebook: Discovery Science; 18th International C Nathalie Japkowicz,Stan Matwin Conference proceedings 2015 Springer International Publishing Switze

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51#
發(fā)表于 2025-3-30 08:38:49 | 只看該作者
52#
發(fā)表于 2025-3-30 12:42:08 | 只看該作者
53#
發(fā)表于 2025-3-30 19:27:05 | 只看該作者
https://doi.org/10.1007/978-3-319-73906-9nsiderable part of on-line scientific literature is still available in layout-oriented data formats, like PDF, lacking any explicit structural or semantic information. As a consequence the bootstrap of textual analysis of scientific papers is often a time-consuming activity. We present the first ver
54#
發(fā)表于 2025-3-31 00:17:26 | 只看該作者
Cinzia Franceschini,Nicola Loperfidoiology, chemistry, or engineering. However, while many applications involve spatial aspects, up?to now only few kernel methods have been designed to take 3D information into account. We introduce a novel kernel called the 3D Neighborhood Kernel. As a first step, we focus on 3D structures of proteins
55#
發(fā)表于 2025-3-31 01:09:21 | 只看該作者
56#
發(fā)表于 2025-3-31 07:08:02 | 只看該作者
Very Short-Term Wind Speed Forecasting Using Spatio-Temporal Lazy Learning,grid of wind farms, which collaborate by sharing information (i.e. wind speed measurements). It accounts for both spatial and temporal correlation of shared information. Experiments show that the presented algorithm is able to determine more accurate forecasts than a state-of-art statistical algorithm, namely auto. ARIMA.
57#
發(fā)表于 2025-3-31 09:58:17 | 只看該作者
Predictive Analysis on Tracking Emails for Targeted Marketing,and two different data sets using different feature sets. Our results demonstrate that it is possible to predict the rate for a targeted marketing email to be opened or not with approximately 78?% F1-measure.
58#
發(fā)表于 2025-3-31 15:17:50 | 只看該作者
Predicting Drugs Adverse Side-Effects Using a Recommender-System,ormation on possible ADRs is only available after the drug is commercially available. As a first step, we propose using prior information on existing interactions through recommendation systems algorithms. We have evaluated our proposal using data from the ADReCS database with promising results.
59#
發(fā)表于 2025-3-31 19:48:27 | 只看該作者
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發(fā)表于 2025-3-31 23:38:13 | 只看該作者
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