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Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, José Luis Balcázar,Francesco Bonchi,Michèle Sebag Conference pr

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A Robustness Measure of Association Rulest a few properties of this robustness, detail its use in practice and show the outcomes of various experiments. Furthermore, we compare our results to classical tools of statistical analysis of association rules. All in all, we present a new perspective on the evaluation of association rules.
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Finding Critical Nodes for Inhibiting Diffusion of Complex Contagions in Social Networksis .-hard. We develop efficient heuristics for these problems and carry out an empirical study of their performance on three well known social networks, namely ., . and .. Our results show that the heuristics perform well on the three social networks.
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Exploration in Relational Worldsn context in which exploitation is promising. Our experimental evaluation shows the effectiveness and benefit of relational exploration over several propositional benchmark approaches on noisy 3D simulated robot manipulation problems.
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Efficient Confident Search in Large Review Corporawers on the specified attributes. We also introduce . (Confident REview Search Tool), a user-friendly implementation of our framework and a valuable tool for any person dealing with large review corpora. The efficacy of our framework is demonstrated through a rigorous experimental evaluation.
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