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Titlebook: Data Analytics and Management in Data Intensive Domains; 21st International C Alexander Elizarov,Boris Novikov,Sergey Stupnikov Conference

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41#
發(fā)表于 2025-3-28 16:58:37 | 只看該作者
https://doi.org/10.1007/978-0-230-80253-7ions from a science foundation. The proposed method is compared with the method based on topic modeling. Experimental studies show that in terms of such metrics as recall, MAP and NDCG, the proposed method is slightly better. In conclusion, the current limitations of the proposed method are discussed.
42#
發(fā)表于 2025-3-28 22:25:46 | 只看該作者
43#
發(fā)表于 2025-3-29 01:35:01 | 只看該作者
On Information Search Measures and Metrics Within Integration of Information Systems on Inorganic Sustems on inorganic substances and materials properties by introducing the relevance graph built on chemical objects. A “chemical similarity” metric and measure are proposed and their properties are discussed.
44#
發(fā)表于 2025-3-29 03:40:09 | 只看該作者
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發(fā)表于 2025-3-29 09:37:27 | 只看該作者
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發(fā)表于 2025-3-29 15:27:59 | 只看該作者
Realization of Different Techniques for Anomaly Detection in Astronomical Databasesive anomaly detection method shows the best performance, while among purely unsupervised techniques Gaussian mixture model and one-class support vector machine methods outperform isolation forest and local outlier factor methods.
47#
發(fā)表于 2025-3-29 18:21:15 | 只看該作者
48#
發(fā)表于 2025-3-29 21:33:03 | 只看該作者
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發(fā)表于 2025-3-30 01:29:25 | 只看該作者
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發(fā)表于 2025-3-30 07:19:00 | 只看該作者
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