One-hot encoding represents every token with a very long vector, and the length of the vector is the size of the dictionary. In the one-hot vector space, two different characters have orthogonal representations and cannot reflect the semantic relationship between tokens. Distributed representation ...
A token tagged as constraint direction demonstrates the relationship between the variables and the limits. For example, these are the some of the most frequently used tokens for constraint direction entity - “at least”, “greater than”, “less than”, “greater than or equal to”, “no ...
A survey on recent named entity recognition and relationship extraction techniques on clinical texts Appl. Sci., 11 (2021) Google Scholar [19] M. G. Sohrab, M. Miwa, Deep exhaustive model for nested named entity recognition, in: Proceedings of the 2018 Conference on Empirical Methods in Natur...
multiple public datasets. Further, Sue et al proposed the RoFormer21model, which uses rotary relative position embedding (ROPE) to achieve relative position embedding using absolute position embedding to better represent the position relationship between token in a sequence. Existing entity recognition met...
Workflow of the proposed system to quantify theCross-modal Context Similarity(CMCS). Part-of-speech tagging is applied to extract textual scene context candidates (Sect.4.1), e.g., nouns from the text. The class names as well as visual probabilities computed by a deep learning approach for ...
Combined with the results of topographic measurements, CFD-post (2022 R1) and Tecplot software were used to make velocity contour maps, flow field maps, bed shear stress maps, and vortex maps to analyze the relationship between the factors, and combined with the physical modeling test, to ...