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Titlebook: Data Integration in the Life Sciences; 13th International C Sören Auer,Maria-Esther Vidal Conference proceedings 2019 Springer Nature Switz

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发表于 2025-3-21 16:12:44 | 显示全部楼层 |阅读模式
书目名称Data Integration in the Life Sciences
副标题13th International C
编辑Sören Auer,Maria-Esther Vidal
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Data Integration in the Life Sciences; 13th International C Sören Auer,Maria-Esther Vidal Conference proceedings 2019 Springer Nature Switz
描述This book constitutes revised selected papers from the 13th International Conference on Data Integration in the Life Sciences, DILS 2018, held in Hannover, Germany, in November 2018..The 5 full, 8 short, 3 poster and 4 demo papers presented in this volume were carefully reviewed and selected from 22 submissions. The papers are organized in topical sections named: big biomedical data integration and management; data exploration in the life sciences; biomedical data analytics; and big biomedical applications. .
出版日期Conference proceedings 2019
关键词artificial intelligence; computational linguistics; data integration; databases; information management;
版次1
doihttps://doi.org/10.1007/978-3-030-06016-9
isbn_softcover978-3-030-06015-2
isbn_ebook978-3-030-06016-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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发表于 2025-3-21 20:51:29 | 显示全部楼层
Yueyu Dong,Fei Dai,Mingming Qinof the annotation process, we propose the use of machine learning to combine the results of different annotation tools. We comparatively evaluate the results of the machine-learning based approach with the results of the single tools and a simpler set-based result combination.
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https://doi.org/10.1007/978-3-030-06016-9artificial intelligence; computational linguistics; data integration; databases; information management;
发表于 2025-3-22 12:01:41 | 显示全部楼层
978-3-030-06015-2Springer Nature Switzerland AG 2019
发表于 2025-3-22 15:17:47 | 显示全部楼层
A Learning-Based Approach to Combine Medical Annotation Resultsof the annotation process, we propose the use of machine learning to combine the results of different annotation tools. We comparatively evaluate the results of the machine-learning based approach with the results of the single tools and a simpler set-based result combination.
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发表于 2025-3-23 02:33:49 | 显示全部楼层
Fei Xu,Fangming Liu,Dekang Zhu,Hai Jin genomic components can often be modeled and visualized in graph structures. In this paper we propose the integration of several data sets into a graph database. We study the aptness of the database system in terms of analysis and visualization of a genome regulatory network (GRN) by running a bench
发表于 2025-3-23 08:29:50 | 显示全部楼层
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