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This deliverable reports on the design and approach of the I-BiDaaS batchprocessing module. This report describes the state of the work done in work package 3 from month 12th until month 18th. During these 6 months, we have advanced in the development of both the batch-processing module and the definition and development of the use cases. As part of the batch-processing module we report advances in the Advance Machine Learning submodule, describing our implementation of the Alternating Direction Method of Multipliers optimization, and advances in the technological components of the platform (Hecuba and the Test Data Fabrication tool), that we are leveraging to support the use cases of the project. We also started with the exploration of how our technological component Qbeast can improve the performance of the machine learning algorithms.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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