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Titlebook: Big Data Analytics; 10th International C Partha Pratim Roy,Arvind Agarwal,R. Uday Kiran Conference proceedings 2022 The Editor(s) (if appli

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樓主: Motion
41#
發(fā)表于 2025-3-28 14:40:09 | 只看該作者
42#
發(fā)表于 2025-3-28 20:03:56 | 只看該作者
Drugomics: Knowledge Graph & AI to Construct Physicians’ Brain Digital Twin to Prevent Drug Side-Effe of death in the US. To overcome this crisis, we have constructed the Drugomics knowledge graphs comprising DDI and DDSI interactions mined from Drugs@FDA, FAERS (FDA Adverse Events Reporting System), PubMed, literature, DailyMed, drug ontology, and other biomedical data sources. We used Artificial
43#
發(fā)表于 2025-3-29 01:46:03 | 只看該作者
44#
發(fā)表于 2025-3-29 03:57:39 | 只看該作者
Community Detection in?Large Directed Graphse present here a new scalable Map-Reduce algorithm to discover PageRank-driven hierarchical community structures in directed graphs. Main features of our approach are that we seek to find a directed community centered around any selected core node of a directed graph, and a community is defined by t
45#
發(fā)表于 2025-3-29 10:46:38 | 只看該作者
46#
發(fā)表于 2025-3-29 15:09:03 | 只看該作者
Discovering Top-k Periodic-Frequent Patterns in?Very Large Temporal Databasesall patterns in a database that satisfy the user-specified . (.) and . (.) constraints. . controls the minimum number of transactions in which a pattern must appear in a database. . controls the maximum time interval within which a pattern must reappear in the database. Setting an appropriate . and
47#
發(fā)表于 2025-3-29 18:21:39 | 只看該作者
https://doi.org/10.1007/978-3-662-28581-7ts in this area. Grand-view Research has calibrated the global AI market at 93.5 billion dollars as of 2021. Further, according to their report, it is expected to grow at a compound annual growth rate (CAGR) of 38.1% from 2022 to 2030. It is believed that nations that adopt and use AI will have a co
48#
發(fā)表于 2025-3-29 22:08:20 | 只看該作者
49#
發(fā)表于 2025-3-30 02:51:46 | 只看該作者
Schlussbetrachtung und Ausblick, as slow speed, long training times, and the local minimum problem. Multi-layer Extreme Learning Machine has overcome these problems by avoiding backpropagation and thus saves a significant amount of training time, ensures global optimal, and can handle a vast quantity of data. The most important ch
50#
發(fā)表于 2025-3-30 04:04:01 | 只看該作者
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