Titlebook: Integrated Uncertainty in Knowledge Modelling and Decision Making; 10th International S Katsuhiro Honda,Bac Le,Youji Kohda Conference proce

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書目名稱Integrated Uncertainty in Knowledge Modelling and Decision Making影響因子(影響力)




書目名稱Integrated Uncertainty in Knowledge Modelling and Decision Making影響因子(影響力)學(xué)科排名




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書目名稱Integrated Uncertainty in Knowledge Modelling and Decision Making網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Integrated Uncertainty in Knowledge Modelling and Decision Making被引頻次




書目名稱Integrated Uncertainty in Knowledge Modelling and Decision Making被引頻次學(xué)科排名




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書目名稱Integrated Uncertainty in Knowledge Modelling and Decision Making年度引用學(xué)科排名




書目名稱Integrated Uncertainty in Knowledge Modelling and Decision Making讀者反饋




書目名稱Integrated Uncertainty in Knowledge Modelling and Decision Making讀者反饋學(xué)科排名

強(qiáng)制性

干旱

Joint Multiple Efficient Neighbors and?Graph Learning for?Multi-view Clusteringng sparsity and connectivity simultaneously is challenging. Multi-view clustering (MC) integrates complementary information from different views. However, most existing methods introduce noise or ignore relevant data structures. This paper introduces a Joint multiple efficient neighbors and Graph (J

avulsion

Maximum-Margin Nearest Prototype Classifiers with?the?Sum-over-Others Loss Function and?a?Performanch is a weighted sum of the inverted margin and a loss function. It is reduced a difference-of-convex optimization problem, and solved using the convex-concave procedure. In our latest study, to overcome limitations of the previous model, we have revised the model in both of the optimization problem

EXCEL

惰性氣體

Harrowing

TouriER: Temporal Knowledge Graph Completion by?Leveraging Fourier Transformsporal information, it poses a complex problem with larger data size, increased complexity in interactions between objects, and a potential for information overlap across time intervals. In this research, we introduce a novel model called TouriER, based on the MetaFormer architecture, to learn tempor

BOAST

Machine Learned KPI Goal Preferences for Explainable AI based Production Sequencinglgorithm for optimization of real-world production sequences. It is also shown how such algorithms can be both parameterized and reparametrized in an explainable ad-hoc and post-hoc manner. The explanations are also used to manage contradictory and counterfactual optimization effects so that uncerta

飛鏢

Unearthing Undiscovered Interests: Knowledge Enhanced Representation Aggregation for?Long-Tail Recoms predominantly focus on suggesting popular items, disregarding the significance of long-tail recommendation and consequently falling short of meeting users’ personalized needs. To this end, we propose a novel approach called Knowledge-enhanced Representation Aggregation for Long-tail Recommendation

調(diào)整

A Novel Methodology for?Real-Time Face Mask Detection Using PSO Optimized CNN Technique lot of precautionary measures are suggested by the World Health Organization (WHO) to prevent the spread of COVID-19, like the use of sanitizers, social distancing, and face masks. Wearing the face-masks incorrectly makes them useless and spreads the virus. In this manuscript, a convolution neural