Titlebook: Inductive Databases and Constraint-Based Data Mining; Sa?o D?eroski,Bart Goethals,Pan?e Panov Book 2010 Springer Science+Business Media, L

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Lo?c Cerf,Bao Tran Nhan Nguyen,Jean-Fran?ois Boulicaut on the buffer occupancy and scheduling delay of a leaky bucket regulated flow have been proved to hold under DRR. However, performance bounds are important for real-time traffic such as video or voice, whereas regarding data traffic average performance indices are meaningful in most of the cases. I

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Arno Siebes,Diyah Puspitaningrumks; this century, however, there has been more emphasis on other kinds of documents, and particularly their design. But no shift in document production has been more sudden than the one that has happened most recently. ConSequently, the last five years have witnessed a substantial movement away from

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Celine Vens,Leander Schietgat,Jan Struyf,Hendrik Blockeel,Dragi Kocev,Sa?o D?eroskilectron micro- graphs. First, many years of work on correcting the resolution-limiting aberrations of electron microscope objectives had shown that these optical impediments to very high resolution could indeed be overcome, but only at the cost of immense exper- imental difficulty; thanks largely to

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Inductive Databases and Constraint-based Data Mining: Introduction and Overviewn discuss constraints and constraint-based data mining in more detail, followed by a discussion on knowledge discovery scenarios. We further give an overview of recent developments in the area, focussing on those made within the IQ project, that gave rise to most of the chapters included in this vol

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Representing Entities in the OntoDM Data Mining Ontologyons, we address the task of constructing an ontology of data mining. Our heavy-weight ontology, named OntoDM, is based on a recently proposed general framework for data mining. It represent entites such as data, data mining tasks and algorithms, and generalizations (resulting from the latter), and a