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Titlebook: Knowledge Discovery in Databases: PKDD 2004; 8th European Confere Jean-François Boulicaut,Floriana Esposito,Dino Ped Conference proceedings

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Strength in Diversity: The Advance of Data Analysis different disciplines have led sometimes to the same analytic tools being developed, but also sometimes to different tools being developed. Some conjectures about likely future developments are given.
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Shape and Size Regularization in Expectation Maximization and Fuzzy Clusteringssians. However, these additional degrees of freedom often reduce the robustness of the algorithm, thus sometimes rendering their application problematic. In this paper we suggest shape and size regularization methods that handle this problem effectively.
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Breaking Through the Syntax Barrier: Searching with Entities and Relationsgraph models involving page regions, tables, sentences, phrases, and real-world-entities. New algorithms will combine probabilistic evidence from diverse features to produce responses that are not URLs or pages, but entities and their relationships, or explanations of how multiple entities are related.
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AutoPart: Parameter-Free Graph Partitioning and Outlier Detectiones practically linearly with the problem size. Further, we propose novel algorithms which use this node group structure to get further insights into the data, by finding outliers and computing distances between groups. Finally, we present experiments on multiple synthetic and real-life datasets, where our methods give excellent, intuitive results.
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