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Titlebook: Data Quality Management with Semantic Technologies; Christian Fürber Book 2016 Springer Fachmedien Wiesbaden 2016 Data Quality Problems.Da

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樓主: foresight
21#
發(fā)表于 2025-3-25 05:23:03 | 只看該作者
22#
發(fā)表于 2025-3-25 10:48:41 | 只看該作者
Data Quality Management with Semantic Technologies
23#
發(fā)表于 2025-3-25 12:40:20 | 只看該作者
Data Quality Management with Semantic Technologies978-3-658-12225-6
24#
發(fā)表于 2025-3-25 16:30:40 | 只看該作者
25#
發(fā)表于 2025-3-25 20:52:18 | 只看該作者
Semantic Technologies,eb. After that, we explain ways to process knowledge representations, such as reasoning, inferencing, and querying. Due to the focus of this thesis, we finally describe how relational databases and ontologies are related.
26#
發(fā)表于 2025-3-26 01:07:47 | 只看該作者
Data Quality in the Semantic Web,e et al., 2001). For example, if the prices of all consumer products were published in a machine-readable format and structure throughout the whole Web, then more complete price comparisons at global scale would be possible with minimal manual effort.
27#
發(fā)表于 2025-3-26 04:37:25 | 只看該作者
Evaluation of the Semantic Data Quality Management Framework (SDQM),, one Semantic Web use case with data from DBpedia, and one use case that examines the capability of SDQM to automatically identify inconsistent data requirements. In the third part of the evaluation, SDQM is compared to a conventional data quality tool.
28#
發(fā)表于 2025-3-26 09:20:30 | 只看該作者
Book 2016 this thesis compares the framework to conventional data quality software. Besides the framework, this thesis delivers important theoretical findings, namely a comprehensive typology of data quality problems, ten generic data requirement types, a requirement-centric data quality management process, and an analysis of related work.?.
29#
發(fā)表于 2025-3-26 16:19:57 | 只看該作者
Specification of Initial Requirements,hodology (DSRM, cf. Peffers et al., 2008) process as explained in section 2.4. We start with describing the required artifacts with a motivating scenario that illustrates the needs related to data quality management. Based on the motivating scenario, we derive initial requirements for the framework.
30#
發(fā)表于 2025-3-26 17:05:04 | 只看該作者
Architecture of the Semantic Data Quality Management Framework (SDQM),management vocabulary (DQM Vocabulary), (4) the data requirements editor, and (5) the reporting layer. The design of the architecture is based on the requirements identified in the previous chapter. The following sections are organized according to these major components of the SDQM.
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