Titlebook: Computational Science and Its Applications – ICCSA 2022 Workshops; Malaga, Spain, July Osvaldo Gervasi,Beniamino Murgante,Chiara Garau Con

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書目名稱Computational Science and Its Applications – ICCSA 2022 Workshops影響因子(影響力)




書目名稱Computational Science and Its Applications – ICCSA 2022 Workshops影響因子(影響力)學(xué)科排名




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書目名稱Computational Science and Its Applications – ICCSA 2022 Workshops網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Science and Its Applications – ICCSA 2022 Workshops被引頻次




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書目名稱Computational Science and Its Applications – ICCSA 2022 Workshops讀者反饋




書目名稱Computational Science and Its Applications – ICCSA 2022 Workshops讀者反饋學(xué)科排名

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https://doi.org/10.1007/978-3-031-58449-7proved this model’s performance by using Natural Language Processing (NLP) and Deep Learning (DL) techniques. This was done by evaluating the same dataset used by the previous researcher to train the proposed model. The overall results show that LSTM outperform both GRU and CNN models in terms of F1

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Sarfraz Nazir,Alessandro Capocchialgorithms. Customer-website interaction is considered a key input variable in creating personalized recommendations. Customers are supposed to use the website and leave interaction data regarding product configurations they’re interested in. To prove the efficiency of this methodology, we developed

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Michael P. Weinstein,R. Eugene Turnerufacturing and transmission line applications. In this pipeline, the Bayesian optimization solution is used to suggest the best combination of hyperparameters for model variables. We analyze four multi-output models, such as Adaptive Boosting, Gradient Boosting, Random Forest and MultiLayer Perceptr

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https://doi.org/10.1007/978-1-4614-3188-6t more effectively. Another gap that we aim to fill is the temporal representation of the facts stored in the knowledge graph. At the best of our knowledge, this is the first attempt to associate the temporal validity to the KG relations. This additional information can be used to further enhance th

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Miguel Esteban,Tomohiro Akiyama,Takashi MinoTherefore, it is considered a necessity to determine appropriate strategies for the use of Metaverse in the educational field and to start determining its widespread effect until the infrastructure of Metaverse matures.

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Natural Language Processing and Deep Learning Based Techniques for Evaluation of Companies’ Privacy proved this model’s performance by using Natural Language Processing (NLP) and Deep Learning (DL) techniques. This was done by evaluating the same dataset used by the previous researcher to train the proposed model. The overall results show that LSTM outperform both GRU and CNN models in terms of F1