Conclusions Experiments on both synthetic and real data demonstrate the effectiveness of the knowledge-fused differential dependency network in revealing the statistically significant rewiring in biological networks. The method efficiently leverages data-driven evidence and existing biological knowledge while ...
Where your enterprise is positioned in the surroundings (what you gather from the environment) determines the nature of the refinement processes, and the specific nature of the artifacts at each level of the pyramid. A data-driven enterprise will gather data from the environment. And that data w...
OpenSPG is a Knowledge Graph Engine developed by Ant Group in collaboration with OpenKG, based on the SPG (Semantic-enhanced Programmable Graph) framework. Core Capabilities: 1) domain model constrained knowledge modeling, 2) facts and logic fused representation, 3) natively support KAG... ...
Additionally, the feature set described in data pre-processing was fused with it, building the sub-model BERT + Fx, two additional models (BERT + IQ, BERT + SC), and the complete model which fusing all features (BERT + IQ + SC). The two additional models will be used to evaluate ...
🙌 This repository collects papers integrating Knowledge Graphs (KGs) and Multi-Modal Learning, focusing on research in two principal aspects: KG-driven Multi-Modal (KG4MM) learning, where KGs support multi-modal tasks, and Multi-Modal Knowledge Graph (MM4KG), which extends KG studies into ...
The object-oriented method is used to establish the process knowledge data model of the heterogeneous models in the CAPP system, and the knowledge base, knowledge logic and the process database driven by the object model are combined to realize the analysis and acquisition of process knowledge. ...
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Finally, the simulation results of the CEPRJ 36-bus system show that the proposed method can accurately give effective ELS measures. Compared with the pure data-driven DRL method, the knowledge-enhanced DRL method is mo...
OpenSPG is a Knowledge Graph Engine developed by Ant Group in collaboration with OpenKG, based on the SPG (Semantic-enhanced Programmable Graph) framework. Core Capabilities: 1) domain model constrained knowledge modeling, 2) facts and logic fused rep
PLMs are also limited in theirreasoningabilities because they are purely data-driven. All these shortcomings of PLMs can be improved by incorporating external knowledge, which leads to what we call Knowledge-Enhanced Pre-trained Language Models (KEPLMs). Fig. 1 shows the advantages of KEPLMs in...