Zobrazeno 1 - 10
of 170 474
pro vyhledávání: '"data preparation"'
Autor:
Bosmans, Lien, Peeperkorn, Jari, Goossens, Alexandre, Lugaresi, Giovanni, De Smedt, Johannes, De Weerdt, Jochen
Object-centric process mining is emerging as a promising paradigm across diverse industries, drawing substantial academic attention. To support its data requirements, existing object-centric data formats primarily facilitate the exchange of static ev
Externí odkaz:
http://arxiv.org/abs/2410.00596
Autor:
Huang, Yixing, Fan, Fuxin, Gomaa, Ahmed, Maier, Andreas, Fietkau, Rainer, Bert, Christoph, Putz, Florian
Cone-beam computed tomography (CBCT) is widely used in interventional surgeries and radiation oncology. Due to the limited size of flat-panel detectors, anatomical structures might be missing outside the limited field-of-view (FOV), which restricts t
Externí odkaz:
http://arxiv.org/abs/2409.08800
Autor:
Zhang, Fengji, Zhang, Zexian, Keung, Jacky Wai, Tang, Xiangru, Yang, Zhen, Yu, Xiao, Hu, Wenhua
Code Smell Detection (CSD) plays a crucial role in improving software quality and maintainability. And Deep Learning (DL) techniques have emerged as a promising approach for CSD due to their superior performance. However, the effectiveness of DL-base
Externí odkaz:
http://arxiv.org/abs/2406.19240
Data scientists develop ML pipelines in an iterative manner: they repeatedly screen a pipeline for potential issues, debug it, and then revise and improve its code according to their findings. However, this manual process is tedious and error-prone.
Externí odkaz:
http://arxiv.org/abs/2404.19591
Autor:
KULIGOWSKA, Karolina1 kkuligowska@wne.uw.edu.pl, KOWALCZUK, Bartłomiej2 b.kowalczuk@tidio.net
Publikováno v:
Journal of Applied Economic Sciences. Fall2024, Vol. 19 Issue 3, p317-325. 9p.
Akademický článek
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Autor:
Bandel, Elron, Perlitz, Yotam, Venezian, Elad, Friedman-Melamed, Roni, Arviv, Ofir, Orbach, Matan, Don-Yehyia, Shachar, Sheinwald, Dafna, Gera, Ariel, Choshen, Leshem, Shmueli-Scheuer, Michal, Katz, Yoav
In the dynamic landscape of generative NLP, traditional text processing pipelines limit research flexibility and reproducibility, as they are tailored to specific dataset, task, and model combinations. The escalating complexity, involving system prom
Externí odkaz:
http://arxiv.org/abs/2401.14019
Autor:
Gagliardelli, Luca, Beneventano, Domenico, Esposito, Marco, Zecchini, Luca, Simonini, Giovanni, Bergamaschi, Sonia, Miselli, Fabio, Miano, Giuseppe
In this paper, we present the data preparation activities that we performed for the Digital Experience Platform (DXP) project, commissioned and supervised by Doxee S.p.A.. DXP manages the billing data of the users of different companies operating in
Externí odkaz:
http://arxiv.org/abs/2312.12902
Autor:
Mozzillo, Angelo, Zecchini, Luca, Gagliardelli, Luca, Aslam, Adeel, Bergamaschi, Sonia, Simonini, Giovanni
Publikováno v:
Proceedings 28th International Conference on Extending Database Technology, EDBT 2025, Barcelona, Spain, March 25-28, 2025 (pp. 337-349)
Data preparation is a trial-and-error process that typically involves countless iterations over the data to define the best pipeline of operators for a given task. With tabular data, practitioners often perform that burdensome activity on local machi
Externí odkaz:
http://arxiv.org/abs/2312.11122