High performance Data mining
Biodiversity and Environment Data Mining
... 4 Data Mining for Biodiversity 4.1 Data Mining Concept Data mining, also known as knowledge discovery from data (KDD), is a set of concepts, methods and tools for the ...
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Software Tracing Comparison Using Data Mining Techniques
... In this way, there are two types of tracepoints: static tracepoints and dynamic tracepoints, [26]. The first type, dynamic tracepoints, do not have any impact when not activated. Linux has had dynamic trace functionality ...
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Data stream management and mining
... the performance of different Data Stream Management ...all data are received by the Data Stream Management System which is in charge of supervising traffic by computing for each vehicle a toll ...
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JetStream: Enabling High Performance Event Streaming across Cloud Data-Centers
... Big Data are expanding the scale and speed at which data analysis is per- ...Big Data, applications process larger data sets, within and across ...fast data transfers across geograph- ...
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BIM-oriented data mining for thermal performance of prefabricated buildings
... the performance gap among actual and simulated building energy ...a high absorbance percentage, which implies the use of natural ventilation to guarantee thermal ...their high effect on setting ...
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A Hybrid Approach for Mining Metabolomic Data
... Since the number of features to propose as predictive biomarkers should be rather small (because of clinical constraints), we rely on the ROC curves of 2, 3, 5 , 10, 20 and 48 of features ranked w.r.t. AUC values. The ...
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Une approche à base d’agents pour Data Mining à travers un ERP
... Plusieurs approches et plateformes ont été proposées pour atteindre ces objectifs de décision qui sont relativement efficaces selon le domaine d’application. Dans cette vision, et pour découvrir des connaissances ...
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High-Performance Computing for Data Analytics
... 2.1. Advantages of probabilistic modelling Drug dissolution system (DDS) models can be broadly split into two categories. Mechanistic models attempt to describe the system precisely, using sets of differential equations, ...
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A Novel Data Compression Techniques for Remote Sensing Data Mining
... Sensing data mining. We provided a methodology for the mining of hyperspectral datasets based on this ...methodology performance is similar to other methodologies found on the literature, ...
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Galois Connections, T-CUBES, and P2P Data Mining
... searching for some closed sets or selected parts of the lattice. Obviously if a close set includes many more students and much fewer courses than any other, these courses are perhaps a little too easy. There were ...
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A Practical Data-Driven Framework for Parallel Data Mining
... A Practical Data-driven Framework for Parallel Data Mining dataset for that task at hand. Three commonly used partition methods are: random partitioning, sequential partitioning, and attribute-based ...
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Spatio-Temporal data mining: From big data to patterns
... 4 Conclusion The challenges associated with spatial and spatio- temporal databases are numerous. Firstly, the se- mantics of extracted patterns must be considered to present experts with patterns which actually meet ...
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Tweet Data Mining: the Cultural Microblog Contextualization Data Set
... entire data set for two users among the most frequent users While the three users have a similar profile with regard to the week days (there is no large difference depending on the week day); they have very ...
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The regulation of Text and Data Mining
... perform data mining on a content accessed legitimately should be considered an abuse of exclusive rights and declared illegal – Technical restrictions to download the content in an open format will also ...
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Data Mining in Ship Construction and operation
... Construct Data Construct Data Construct Data Construct Data Derived Attributes Generated Records Integrate Data Integrate Data Integrate Data Integrate Data Merged Data Format Data Forma[r] ...
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Mining gene expression data using domain knowledge
... in data mining, efficient and scalable techniques for mining relevant patterns from large datasets are ...of high-throughput methods for quantitative monitoring of gene expression has ...
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Unveiling Crucivirus Diversity by Mining Metagenomic Data
... m Structural Biology Research Unit, Department of Clinical Laboratory Sciences, University of Cape Town, Rondebosch, Cape Town, South Africa ABSTRACT The discovery of cruciviruses revealed the most explicit example of a ...
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Suggesting valid pharmacogenes by mining linked data
... using data from PharmGKB, DrugBank, and protein–protein interac- tions from InWeb ...achieve high F-measure and AUC ...patient data to instantiate a DL knowledge base, then extracted association ...
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StreamDM: Advanced Data Mining in Spark Streaming
... It also allows streams which may change their underlying format at any time. In general, the task process proceeds as follows. First, the streaming data from DStream is read and parsed by a Reader class. Then, the ...
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Data-mining natural language materials syntheses
... In each case we seek a binary classifier which separates the desirable outcome (e.g. symmetry equals tetragonal, or morphology equals 2D) from the other outcomes (e.g. “not 2D”). In each subplot of Figure 3, the receiver ...
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