This paper explains our participation in task 1of the CASE 2021 shared task. This task is about multilingual event extraction from the news. We focused on sub-task 4, event information extraction. This sub-task has a small training dataset, and we fine-tuned a multilingual BERT to solve this sub-task.
Continue readingA Combined Rule-Based and Machine Learning Approach for Automated GDPR Compliance Checking
The General Data Protection Regulation (GDPR) requires data controllers to implement end-to-end compliance. Controllers must therefore ensure that the terms agreed with the data subject and their own obligations under GDPR are respected in the data flows from data subject to controllers, processors and sub-processors (i.e. data supply chain).
Continue readingDMMM: Data Management Maturity Model
The assessment of the digital transformation progress is essential to understand and undertake in order to evaluate the level of maturity of data-driven companies in terms of data capabilities and to plan for improvement actions.
Continue readingA Survey of Maturity Models in Data Management
Maturity models are helpful business tools that refine and develop how organizations conduct their businesses and benchmark their maturity status against a scale or with industry peers. They serve to prioritize the actions for improvement better and control the progress in reaching the target maturity stage.
Continue readingMIC: Multi-view Image Classifier using Generative Adversarial Networks for Missing Data Imputation
In this paper, we propose a framework for image classification tasks, named MIC, that takes as input multi-view images, such as RGB-T images for surveillance purposes. We combine auto-encoder and generative adversarial network architectures to ensure the multi-view embedding in a common latent space.
Continue readingTowards a Continuous Evaluation of Calibration
For safety-critical systems involving AI components (such as in planes, cars, or healthcare), safety and associated certification tasks are one of the main challenges, which can become costly and difficult to address.
One key aspect is to ensure that the decisions a machine-learning classifier makes are properly calibrated.
Continue readingPadhoc: a Computational Pipeline for Pathway Reconstruction On The Fly
Molecular pathway databases represent cellular processes in a structured and standardized way. These databases support the community-wide utilization of pathway information in biological research and the computational analysis of high-throughput biochemical data. We present Padhoc, a pipeline for pathway ad hoc reconstruction.
Continue reading2Be3-Net : Combining 2D and 3D convolutional neural networks for 3D PET scans predictions
Radiomics is the main approach used to develop predictive models based on 3D Positron Emission Tomography (PET) scans of patients suffering from cancer. We propose a deep learning architecture associating a 2D feature extractor to a 3D CNN predictor.
Continue readingPrivacy Policy Classification with XLNet
The popularisation of privacy policies has become an attractive subject of research in recent years, notably after the General Data Protection Regulation came into force in the European Union. While GDPR gives Data Subjects more rights and control over the use of their personal data, length and complexity of privacy policies can still prevent them from exercising those rights. An accepted way to improve the interpretability of privacy policies is…
Continue readingTowards Privacy Policy Conceptual Modeling
After GDPR enforcement in May 2018, the problem of implementing privacy by design and staying compliant with regulations has been more prominent than ever for businesses of all sizes, which is evident from frequent cases against companies and significant fines paid due to non-compliance. Consequently, numerous research works have been emerging in this area….
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