Thèse de doctorat : Université de Fribourg, 2020.
This thesis intends to present some advances in fuzzy statistical analyses. A particular distance between fuzzy numbers called the signed distance, seems to be appealing because of its directional property. It has the ability of describing the direction of travel between two fuzzy numbers. In addition, it has been often used as a fuzzy ranking tool or a defuzzification operator. Despite the...
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Thèse de doctorat : Université de Fribourg, 2020 ; no. 2192.
We live in an Information Age, facing a rapid increase in the amount of information that is exchanged. This permanently growing amount of data makes the ability to store, analyze, and act upon information a primary concern (in addition to the obvious privacy, legal and ethical issues that are related), raising the question: “How can one consume Big Data and transformit into actionable...
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In: 2019 6th Swiss Conference on Data Science (SDS), 2019, p. 63–68
One of the major difficulties in applying distant supervision to relation extraction is class imbalance, as the distribution of relations appearing in text is heavily skewed. This is particularly damaging for the multi-instance variant of relation extraction. In this work, we introduce a new model called Aggregated Piecewise Convolutional Neural Networks, or APCNN, to address this problem....
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In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019, p. 1162–1172
Embeddings have become a key paradigm to learn graph representations and facilitate downstream graph analysis tasks. Existing graph embedding techniques either sample a large number of node pairs from a graph to learn node embeddings via stochastic optimization, or factorize a high-order proximity/adjacency matrix of the graph via expensive matrix factorization. However, these techniques...
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In: The Semantic Web – ISWC 2019, 2019, p. 453-469
Collaborative Knowledge Graph platforms allow humans and automated scripts to collaborate in creating, updating and interlinking entities and facts. To ensure both the completeness of the data as well as a uniform coverage of the different topics, it is crucial to identify underrepresented classes in the Knowledge Graph. In this paper, we tackle this problem by developing statistical techniques...
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Thèse de doctorat : Université de Fribourg, 2018 ; no. 2098.
When entering a new era of digital societies, a vast number of digital footprints left by users becomes a new source of the economic good. A heavy exploitation of Big data, artificial intelligence, cognitive computing, amongst others, makes the data more valuable implying that the risk to people’s privacy will be ever-increasing. Especially, when their privacy decisions are confronted with...
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Mémoire de master : Université de Fribourg, 2014.
The authorship attribution is the practice of inferring the author of a given text based on the analysis of her/his writing style. It has been largely used in literature work disputes but it has other interesting applications such as forensics and plagiarism detection. The purpose of this project is to experiment and present a solution that can identify the authors of a given corpora. We have two...
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In: Potato Research, 2002, vol. 45, no. 2-4, p. 177-185
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In: Journal of Low Temperature Physics, 2011, vol. 165, no. 3-4, p. 166-176
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In: Transition Metal Chemistry, 2003, vol. 28, no. 1, p. 37-42
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