Titlebook: New Trends in Databases and Information Systems; Mykola Pechenizkiy,Marek Wojciechowski Conference proceedings 2013 Springer-Verlag Berlin

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灰心丧气

Comparing Block Ensembles for Data Streams with Concept Driftemble after processing each successive block of incoming examples, while the other ensembles are additionally extended by different drift detectors. Experiments show that these extensions improve classification accuracy, in particular for sudden changes occurring within the block, as well as reduce

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Adapting Travel Time Estimates to Current Traffic Conditionstarts with collecting floating car data, i.e. multi-channel stream data sent in from moving cars. These dynamic data are then processed in an elaborate, multistage procedure, aimed at estimating the travel time and constituting an essential component of optimal route planning, which can effectively

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SONCA: Scalable Semantic Processing of Rapidly Growing Document Storesd indexing solutions are called for. In this paper we present the architecture and the data model of such a system. SONCA (Search based on ONtologies and Compound Analytics) is a platform to implement and exploit intelligent algorithms identifying relations between various types of objects (publicat

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Collective Classification Techniques: An Experimental Studynown nodes and the network structure only. Three collective classification algorithms were described and examined in the paper: Iterative Classification (ICA), Gibbs Sampling (GS) and Loopy Belief Propagation (LBP). Experiments on various networks revealed that greater number of output classes decre

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Evaluation of Stream Data by Formal Concept Analysisess. The main aim of this paper is to show possibilities of using FCA to detect anomalies in the data. Our attitude is based on the fact that although during the production process a large amount of input data is obtained, the size of conceptual lattice is relatively small, and therefore, it is poss