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Titlebook: Advances in Combining Intelligent Methods; Postproceedings of t Ioannis Hatzilygeroudis,Vasile Palade,Jim Prentzas Conference proceedings 2

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https://doi.org/10.1007/978-3-030-50100-6 forecasting stock returns. The purpose of this paper is to present a method, based on a combination of a Naïve Bayes classifier and the n-gram probabilistic language model, which can create a sentiment index for specific stocks and indices of the New York Stock Exchange. An economic useful proxy fo
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https://doi.org/10.1007/978-3-031-34793-1ntations. These real-world problems generate new instances for the classical, academic problems as well as new data collections that can be used for assessing the available solving packages. This paper focuses on the Traveling Salesman Problem, which is one of the most studied combinatorial optimiza
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,Forecast: Totalschaden möglich, to their knowledge level. In order to provide exercises and learning activities of appropriate difficulty, their difficulty level should be accurately and consistently determined. In this work, we present a neuro-fuzzy and a neuro-symbolic approaches that are used to determine the difficulty level
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