Attention mechanismDrug-Drug interaction extractionLong short-term memoryRelation extractionTaking multiple drugs at the same time can increase or decrease each drug's effectiveness or cause side effects. These drug-drug interactions (DDIs) may lead to an increase in the cost of medical care or ...
Duan YH, Li HH, He MQ, Zhao DD (2021) A BiGRU Autoencoder Remaining Useful Life Prediction Scheme With Attention Mechanism and Skip Connection. IEEE Sens J 21(9):10905–10914. https://doi.org/10.1109/JSEN.2021.3060395 Article Google Scholar Xue B, Xu FM, Huang X, Xu ZB, Zhang X...
Joint Entity Relation Extraction Based on LSTM via Attention Mechanism Entity relation extraction holds a significant role in extracting structured information from unstructured text, serving as afoundational component for var... X Cao,Q Shao - 《Arabian Journal for Science & Engineering》 被引量: 0...
To complete the process of converting a CFG into a graph embedding, it is first necessary to obtain the corresponding instruction vector by looking up thex2vdictionary (“Common vector space embedding”). Then utilizes the LSTM with a self-attention mechanism to complete the basic block embedding...
Attention-Based Learning for Predicting Drug-Drug Interactions in Knowledge Graph Embedding Based on Multisource Fusion Information Drug combinations can reduce drug resistance and side effects and enable the improvement of disease treatment efficacy. Therefore, how to effectively ident... Y Li,ZH You,...
The paper pays particular attention to requirements for incremental and uncertain environments, and to interrelationships among concept purpose, concept representation, and concept learning. DOI: 10.1111/j.1467-8640.1987.tb00213.x 年份: 1987
In two experiments using spatial probes, we measured the temporal and spatial interactions between top-down control of attention and bottom-up interference... MS Kim,KR Cave - 《Perception & Psychophysics》 被引量: 357发表: 1999年 Continuity-based and discontinuity-based segmentation in transparent...
Although many task allocation approaches have been presented to deal with this multi-agent task allocation problem, the similarity among tasks has not been paid much attention. Hence in this paper, we propose an efficient task similarity-based learning approach for task allocation in multi-agent ...
leading to a slowdown at the retrieval site in the activation-based model, and/or to misretrieval in both the activation-based and the direct-access model. In the DA model, which assumes backtracking as a key resource in parsing, resource reductions could disrupt this mechanism and lead to ...
a two-sided attention mechanism is proposed to encode the interaction strength between each compound substructure and protein substructure pair. In the second step, a feature encoder network is learned to improve the generalizability of the model by utilizing an adversarial domain adaptation technique. ...