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Titlebook: Advances in Intelligent Data Analysis XVII; 17th International S Wouter Duivesteijn,Arno Siebes,Antti Ukkonen Conference proceedings 2018 S

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Information Science and Knowledge Managemented by manually matching some POIs. To mitigate this, we have taken advantage of the Crosswalk API, available at the time we started our project, which allowed us to retrieve already matched POI data from different sources in US territory. We trained and tested our model with a dataset containing Fac
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https://doi.org/10.1007/978-1-4020-3095-6ere selected. The obtained results showed that Support Vector Machines imputation ensures the best classification performance while Multiple Imputation by Chained Equations performs better in terms of imputation quality.
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Classifying Scientific Documents, factors to generate possible configurations and prove crucial for contextualising the proposed approach. Empirically, we observe that the predicted itineraries are more accurate than standard path planning algorithms.
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The Interplanetary Medium Familylogical variation. We demonstrate how non-parametric models can help to quantify key properties of a dynamical system when the actual data-generating mechanisms are largely unknown. Such properties include the locations of stable states, resilience of the system, and the levels of stochastic fluctua
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Fact Checking from Natural Text with Probabilistic Soft Logic978-3-642-71449-8
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Training Neural Networks to Distinguish Craving Smokers, Non-craving Smokers, and Non-smokers978-3-8348-9414-4
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Pushing the Envelope in Overlapping Communities Detection978-3-662-62066-3
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