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

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Learning to Have Fune of defeating strong human players. Most of the literature has been devoted to two-player, perfect information games—games where the research results have little wide-spread applicability. However, over the past few years the need for improved AI techniques have become apparent in commercial comput

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Challenges of Urban Sensingntly at the stage of mobile computing. This trend shows several aspects consistent in the evolution of computing including the increasing hardware miniaturization of the computing units and an increasing emphasis of the role of communication between the computing units – “networking”. In addition fr

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Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomicshe task is relevant for several application domains. This paper presents an empirical study of decision tree approaches to HMC in the area of functional genomics. We compare learning a single HMC tree (which makes predictions for all classes together) to learning a set of regular classification tree

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Clustering Scientific Literature Using Sparse Citation Graph Analysisvised learning tasks. However, the ability to identify distinct clusters of documents based on link graph analysis is proportional to the density of the graph and depends on the availability of the linking and/or linked documents in the collection. In this paper, we present an information theoretic

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VOGUE: A Novel Variable Order-Gap State Machine for Modeling Sequencesata modeling. VOGUE relies on a novel Variable-Gap Sequence mining method (VGS), to mine frequent patterns with different lengths and gaps between elements. It then uses these mined sequences to build the state machine. We applied VOGUE to the task of protein sequence classification on real data fro

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