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Enhancing molecular property prediction through data integration and consistency assessment. [PDF]
Parrondo-Pizarro R +4 more
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HoloFoodR: a statistical programming framework for holo-omics data integration workflows. [PDF]
Borman T +7 more
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Computational approaches to multimodal data integration in rheumatoid arthritis: from data landscape to clinical translation. [PDF]
Xu D, Tang Y, Luo J, Wen C.
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2013 IEEE 29th International Conference on Data Engineering (ICDE), 2013
The Big Data era is upon us: data is being generated, collected and analyzed at an unprecedented scale, and data-driven decision making is sweeping through society. Since the value of data explodes when it can be linked and fused with other data, addressing the big data integration (BDI) challenge is critical to realizing the promise of Big Data.
Xin Luna Dong, Divesh Srivastava
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The Big Data era is upon us: data is being generated, collected and analyzed at an unprecedented scale, and data-driven decision making is sweeping through society. Since the value of data explodes when it can be linked and fused with other data, addressing the big data integration (BDI) challenge is critical to realizing the promise of Big Data.
Xin Luna Dong, Divesh Srivastava
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Abstraction in Data Integration
2021 36th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), 2021Data integration provides a unified and abstract view over a set of existing data sources. The typical architecture of a data integration system comprises the global schema, which is the structure for the unified view, the source schema, and the mapping, which is a formal account of how data at the sources relate to the global view.
Cima G. +3 more
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Proceedings of the 2021 International Conference on Management of Data, 2021
We are witnessing the widespread adoption of deep learning techniques as avant-garde solutions to different computational problems in recent years. In data integration, the use of deep learning techniques has helped establish several state-of-the-art results in long standing problems, including information extraction, entity matching, data cleaning ...
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We are witnessing the widespread adoption of deep learning techniques as avant-garde solutions to different computational problems in recent years. In data integration, the use of deep learning techniques has helped establish several state-of-the-art results in long standing problems, including information extraction, entity matching, data cleaning ...
openaire +1 more source

