Holistic, Efficient, and Real-time Cleaning of Heterogeneous Data
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Core to many scientific and analytics applications are spatial data capturing the position or shape of objects in space, and time series recording the values of a process over time. Effective analysis of such data requires a shift from confirmatory pipelin ...
Data is pervasive in today's world and has actually been for quite some time. With the increasing volume of data to process, there is a need for faster and at least as accurate techniques than what we already have. In particular, the last decade recorded t ...
The phenomenal growth of graph data from a wide variety of real-world applications has rendered graph querying to be a problem of paramount importance. Traditional techniques use structural as well as node similarities to find matches of a given query grap ...
Text summarization is considered as a challenging task in the NLP community. The availability of datasets for the task of multilingual text summarization is rare, and such datasets are difficult to construct. In this work, we
build an abstract text summari ...
Association for Computational Linguistics (ACL)2019
The evolution of technologies makes surveying accessible to a broader community of professionals and students. Therefore, teaching geomatics is a continuous challenge. This article presents an original pedagogical approach based on a teaching unit gatherin ...
This article studies the Cauchy problem for systems of semi-linear wave equations on R3+1 with nonlinear terms satisfying the null conditions. We construct future global-in-time classical solutions with arbitrarily large initial energy. The choice of the l ...
Burtscher, Martin, Michael Philadelphy, Hannes Gatterer, Johannes Burtscher, Martin Faulhaber, Werner Nachbauer, and Rudolf Likar. Physiological responses in humans acutely exposed to high altitude (3480 m): Minute ventilation and oxygenation are predictiv ...
Apartment searching has been a hot demand all over the world. Understanding the apartment structure will significantly contribute to simplifying the searching process. In this project, the fully convolutional networks are applied to generate semantic segme ...
We propose fingerprinting, a new technique that consists in constructing compact, fast-to-compute and privacy-preserving binary representations of datasets. We illustrate the effectiveness of our approach on the emblematic big data problem of K-Nearest-Nei ...
The recent explosion in the number and size of spatio-temporal data sets from urban environments and social sensors creates new opportunities for data-driven approaches to understand and improve cities. Visual analytics systems like Urbane aim to empower d ...
