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Titlebook: Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Grow; 14th International C Stanis?aw Koziel

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樓主: choleric
21#
發(fā)表于 2025-3-25 04:54:40 | 只看該作者
22#
發(fā)表于 2025-3-25 09:31:51 | 只看該作者
Covering Approach to Action Rule Learningal of a novel method for induction of action rules directly from a dataset. The proposed algorithm follows the so-called covering schema and employs a pruning procedure, thus being able to produce comprehensible rule sets. An experimental study shows that the proposed method is able to discover strong actions of superior accuracy.
23#
發(fā)表于 2025-3-25 14:13:22 | 只看該作者
Socioeconomic Inequality in AchievementIn the paper, a modified dynamic programming approach for optimization of decision rules relative to length is studied. Experimental results connected with length of approximate decision rules, size of a directed acyclic graph, and accuracy of classifiers, are presented.
24#
發(fā)表于 2025-3-25 17:54:20 | 只看該作者
25#
發(fā)表于 2025-3-25 20:58:04 | 只看該作者
Mark L. Savickas,Suzanne Savickasilarity of the Cartesian product of all records, which is called pair-wise ER and leads to quadratic time complexity. Faced with an exploding data volume, pair-wise ER is challenged to achieve high efficiency and scalability. To tackle this challenge, parallel computing is proposed for speeding up t
26#
發(fā)表于 2025-3-26 03:43:18 | 只看該作者
Itamar Gati,Nimrod Levin,Shiri Landman-Talnt premises of cancer occurrence. In this paper a set of data mining tasks is defined that joins the observed genes mutation with the specific cancer type observation. Due to the high computational complexity of this kind of data a Hadoop ecosystem cluster was developed to perform the required calcu
27#
發(fā)表于 2025-3-26 05:59:14 | 只看該作者
Itamar Gati,Nimrod Levin,Shiri Landman-Taltment of patients. 3D protein structure similarity searching is one of the important exploration processes performed in structural bioinformatics. However, the process is time-consuming and requires increased computational resources when performed against large repositories. In this paper, we show t
28#
發(fā)表于 2025-3-26 08:34:39 | 只看該作者
https://doi.org/10.1007/978-1-4020-5776-2It was developed on the basis of the Big Data technology, allowing not only to process the streaming data but also for performing the batch analyses. The results of data processing are presented in the form of reports and dashboards. The work contains a case study presenting an implementation of the
29#
發(fā)表于 2025-3-26 13:21:38 | 只看該作者
30#
發(fā)表于 2025-3-26 20:26:46 | 只看該作者
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