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Titlebook: Advances in Databases and Information Systems; 24th European Confer Jérôme Darmont,Boris Novikov,Robert Wrembel Conference proceedings 2020

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https://doi.org/10.1007/978-90-481-9864-1on on tight upper bound for the number of nodes in this tree. Instead, a very loose upper bound of . (where . is the number of distinct items in the database) is used. In this paper, we provide a tighter upper bound for the number of nodes in a closed form solution. This result is illustrated in the
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Signalling Mechanisms in Platyhelminths,ms for CFPQ are actively developed, but J. Kuijpers et al. have recently concluded, that existing algorithms are not performant enough to be used in real-world applications. Thus the development of new algorithms for CFPQ is justified. In this paper, we provide a new CFPQ algorithm which is based on
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https://doi.org/10.1007/978-94-017-0998-9 this centralization is often less expensive than the communication of extracted patterns from the different nodes. To circumvent this difficulty, this paper revisits the problem of pattern mining in distributed databases by benefiting from pattern sampling. Specifically, we propose the algorithm .
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Protein Disassembly by Hsp40-Hsp70are intended to operate on relation instances for a given relational schema with a functional dependency, we are then challenged to generate appropriate sample instances of increasing size. Moreover, studying the impact of varying the sizes of the attribute domains might be important. We focus on se
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Robert T. Youker,Jeffrey L. Brodskyaph-based methods have outperformed other ones in the literature of approximate similarity search. However, a graph employed on a dataset may present different behaviors depending on its parameters. Therefore, finding a suitable graph configuration is a time-consuming task, due to the necessity to b
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https://doi.org/10.1007/978-0-387-39717-7ontent features and news propagation features. In this study, we focus on the user spreading news behaviors on social media platforms and aim to detect fake news more effectively with more accurate data reliability assessment. We introduce Subjective Opinions into reliability evaluation and proposed
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