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Titlebook: Advanced Data Mining and Applications; 18th International C Weitong Chen,Lina Yao,Xue Li Conference proceedings 2022 The Editor(s) (if appl

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21#
發(fā)表于 2025-3-25 07:16:19 | 只看該作者
https://doi.org/10.1007/978-3-663-08164-7reality, data can have hidden connections. Therefore, in this research, a new model has been presented that can find hidden relationships between two medical concepts by using MetaMap and appropriate text-mining techniques. Specifically, the model creates a new comprehensive index structure and can
22#
發(fā)表于 2025-3-25 11:04:33 | 只看該作者
23#
發(fā)表于 2025-3-25 13:01:18 | 只看該作者
24#
發(fā)表于 2025-3-25 18:08:13 | 只看該作者
25#
發(fā)表于 2025-3-25 23:33:11 | 只看該作者
26#
發(fā)表于 2025-3-26 02:50:52 | 只看該作者
Fabian Neubauer,Albert E. Frieder Dr.s to share and discuss their opinions about the situation. Twitter is one such platform for public conversation around the coronavirus pandemic, the spread of disease, vaccination, non-pharmaceutical interventions, and many other discussions. In this study, we use Twitter social medial data for sent
27#
發(fā)表于 2025-3-26 07:52:56 | 只看該作者
Adrian Lottenbach,Elmar Perroulaze-constrained nature of the sensor nodes used in the IoT makes them vulnerable to various attacks. Hence, it is important to monitor network traffic information to accurately and promptly identify threats. In this paper, using a machine learning-based framework for learning and detecting such attack
28#
發(fā)表于 2025-3-26 12:30:33 | 只看該作者
Adrian Lottenbach,Elmar Perroulazs, gateways and clouds to digitalize and automate traditional farming methods. Due to the open deployment and wide range accessibility, SA systems face a new attack surface that may lead to security and privacy concerns. It is expected that the cyber security and data science research communities wi
29#
發(fā)表于 2025-3-26 12:58:12 | 只看該作者
https://doi.org/10.1007/978-3-642-34784-9he explosive use of smartphones. Consequently, modern social networks have reached a significant number of users, making their size huge. Thereby scaling over such large data remains a challenging task. Reducing social networks’ size is a key task in social network analysis to deal with this data co
30#
發(fā)表于 2025-3-26 19:40:06 | 只看該作者
Adrian Lottenbach,Elmar Perroulazgestions in many educational applications such as optimal study order generating, curriculum design and course evaluation. However, there are no consistent datasets for concept map research. In this work, we aim to build a comprehensive dataset for learning concept maps. Specifically, we collect 129
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