The input of a network is the key problem for Chinese word sense disambiguation utilizing the neural network. This paper presents an input model of the neural network that calculates the mutual information between con...The input of a network is the key problem for Chinese word sense disambiguation utilizing the neural network. This paper presents an input model of the neural network that calculates the mutual information between contextual words and the ambiguous word by using statistical methodology and taking the contextual words of a certain number beside the ambiguous word according to (-M,+N).The experiment adopts triple-layer BP Neural Network model and proves how the size of a training set and the value of Mand Naffect the performance of the Neural Network Model. The experimental objects are six pseudowords owning three word-senses constructed according to certain principles. The tested accuracy of our approach on a closed-corpus reaches 90.31%, and 89.62% on an open-corpus. The experiment proves that the Neural Network Model has a good performance on Word Sense Disambiguation.展开更多
Electroencephalographic studies using graph theoretic analysis have found aberrations in functional connectivity in children with developmental dyslexia.However,how the training with visual tasks can change the functi...Electroencephalographic studies using graph theoretic analysis have found aberrations in functional connectivity in children with developmental dyslexia.However,how the training with visual tasks can change the functional connectivity of the semantic network in developmental dyslexia is still unclear.We looked for differences in local and global topological properties of functional networks between 21 healthy controls and 22 dyslexic children(8–9 years old)before and after training with visual tasks in this prospective case-control study.The minimum spanning tree method was used to construct the subjects’brain networks in multiple electroencephalographic frequency ranges during a visual word/pseudoword discrimination task.We found group differences in the theta,alpha,beta and gamma bands for four graph measures suggesting a more integrated network topology in dyslexics before the training compared to controls.After training,the network topology of dyslexic children had become more segregated and similar to that of the controls.In theθ,αandβ1-frequency bands,compared to the controls,the pre-training dyslexics exhibited a reduced degree and betweenness centrality of the left anterior temporal and parietal regions.The simultaneous appearance in the left hemisphere of hubs in temporal and parietal(α,β1),temporal and superior frontal cortex(θ,α),parietal and occipitotemporal cortices(β1),identified in the networks of normally developing children was not present in the brain networks of dyslexics.After training,the hub distribution for dyslexics in the theta and beta1 bands had become similar to that of the controls.In summary,our findings point to a less efficient network configuration in dyslexics compared to a more optimal global organization in the controls.This is the first study to investigate the topological organization of functional brain networks of Bulgarian dyslexic children.Approval for the study was obtained from the Ethics Committee of the Institute of Neurobiology and the Institute for Population and Human Studies,Bulgarian Academy of Sciences(approval No.02-41/12.07.2019)on March 28,2017,and the State Logopedic Center and the Ministry of Education and Science(approval No.09-69/14.03.2017)on July 12,2019.展开更多
文摘The input of a network is the key problem for Chinese word sense disambiguation utilizing the neural network. This paper presents an input model of the neural network that calculates the mutual information between contextual words and the ambiguous word by using statistical methodology and taking the contextual words of a certain number beside the ambiguous word according to (-M,+N).The experiment adopts triple-layer BP Neural Network model and proves how the size of a training set and the value of Mand Naffect the performance of the Neural Network Model. The experimental objects are six pseudowords owning three word-senses constructed according to certain principles. The tested accuracy of our approach on a closed-corpus reaches 90.31%, and 89.62% on an open-corpus. The experiment proves that the Neural Network Model has a good performance on Word Sense Disambiguation.
基金The study was supported by the National Science Fund of the Ministry of Education and Science(project DN05/14-2016,to JAD).
文摘Electroencephalographic studies using graph theoretic analysis have found aberrations in functional connectivity in children with developmental dyslexia.However,how the training with visual tasks can change the functional connectivity of the semantic network in developmental dyslexia is still unclear.We looked for differences in local and global topological properties of functional networks between 21 healthy controls and 22 dyslexic children(8–9 years old)before and after training with visual tasks in this prospective case-control study.The minimum spanning tree method was used to construct the subjects’brain networks in multiple electroencephalographic frequency ranges during a visual word/pseudoword discrimination task.We found group differences in the theta,alpha,beta and gamma bands for four graph measures suggesting a more integrated network topology in dyslexics before the training compared to controls.After training,the network topology of dyslexic children had become more segregated and similar to that of the controls.In theθ,αandβ1-frequency bands,compared to the controls,the pre-training dyslexics exhibited a reduced degree and betweenness centrality of the left anterior temporal and parietal regions.The simultaneous appearance in the left hemisphere of hubs in temporal and parietal(α,β1),temporal and superior frontal cortex(θ,α),parietal and occipitotemporal cortices(β1),identified in the networks of normally developing children was not present in the brain networks of dyslexics.After training,the hub distribution for dyslexics in the theta and beta1 bands had become similar to that of the controls.In summary,our findings point to a less efficient network configuration in dyslexics compared to a more optimal global organization in the controls.This is the first study to investigate the topological organization of functional brain networks of Bulgarian dyslexic children.Approval for the study was obtained from the Ethics Committee of the Institute of Neurobiology and the Institute for Population and Human Studies,Bulgarian Academy of Sciences(approval No.02-41/12.07.2019)on March 28,2017,and the State Logopedic Center and the Ministry of Education and Science(approval No.09-69/14.03.2017)on July 12,2019.
