Titlebook: Knowledge Discovery in Databases: PKDD 2006; 10th European Confer Johannes Fürnkranz,Tobias Scheffer,Myra Spiliopoul Conference proceedings

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Arthr-

Learning Parameters in Entity Relationship Graphs from Ranking Preferences works for). In addition, nodes contain text snippets. Extending from vector-space information retrieval, we wish to automatically learn ranking function for searching such typed graphs. User input is in the form of a partial preference order between pairs of nodes, associated with a query. We prese

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Detecting Fraudulent Personalities in Networks of Online Auctioneersvolent auction users try to abuse them by cheating others. In this paper we propose a novel method, . (.), to model the techniques that fraudsters typically use to carry out fraudulent activities, and to detect fraudsters preemptively. Our key contributions are: (a) we mine . (e.g., number of transa

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Measuring Constraint-Set Utility for Partitional Clustering Algorithms constraints to clustering improves performance, with respect to the true data labels. However, in most of these experiments, results are averaged over different randomly chosen constraint sets, thereby masking interesting properties of individual sets. We demonstrate that constraint sets vary signi

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CLASH

e data. The task of inverse optimal control is to identify the precise underlying objective function that is optimized in an observed motion. The presented methods can cope with partial and imprecise measurements of the state variables which is typically the case for motion capture recordings. We in