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Titlebook: Information Search, Integration, and Personalization; 12th International W Dimitris Kotzinos,Dominique Laurent,Rin-ichiro Tan Conference pr

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21#
發(fā)表于 2025-3-25 05:20:00 | 只看該作者
22#
發(fā)表于 2025-3-25 08:19:45 | 只看該作者
23#
發(fā)表于 2025-3-25 14:14:43 | 只看該作者
Big Research Data Integration exploratory studies carried out by research teams. It briefly overviews the technological challenges to be faced in order to successfully carry out the traditional approach to data integration. Then, three important application scenarios are described in terms of their main characteristics that hea
24#
發(fā)表于 2025-3-25 17:31:04 | 只看該作者
25#
發(fā)表于 2025-3-25 20:31:34 | 只看該作者
A Domain-Independent Ontology for Capturing Scientific Experimentslity of scientific experiments in laboratories. While useful, existing solutions suffer from some limitations when it comes to supporting scientists. Indeed, it is up?to him/her to identify which ontologies to use, which fragments of those ontologies are useful for his experiments and how to combine
26#
發(fā)表于 2025-3-26 03:51:34 | 只看該作者
Email Business Activities Extraction and Annotationeered for understanding the undocumented business process activities and their corresponding metadata. Our goal in this paper is to recast emails into business activity centric resources. We describe an approach that is able to discover business process activities from emails. In addition, for each
27#
發(fā)表于 2025-3-26 06:56:59 | 只看該作者
28#
發(fā)表于 2025-3-26 11:03:42 | 只看該作者
Toward FPGA-Based Semantic Caching for Accelerating Data Analysis with Spark and HDFS architecture for querying big Databases. This architecture combines the advantages of the HDFS for the management of huge amount of data and the fast processing of queries of Spark SQL. It also benefits of the processing efficiency of the hardware acceleration of FPGAs and of the semantic caching a
29#
發(fā)表于 2025-3-26 12:40:51 | 只看該作者
A First Experimental Study on Functional Dependencies for Imbalanced Datasets Classificationributed. This causes many problems for classification algorithms trained on such datasets, as they are often biases towards the majority class. Moreover, the minority class often yields more interest for data scientist, when at the same time it is also the hardest to predict. Many different approach
30#
發(fā)表于 2025-3-26 18:11:45 | 只看該作者
ansformation programs in organizations. It rejects the idea that successful organizations are ‘rational systems’ conforming to scripts laid down by leaders, and it places dialogue and co-creation – ‘reciprocal 978-3-319-86501-0978-3-319-58889-6
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