[PDF] Top 20 A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network
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A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network
... related model TransE on both experimental datasets, es- pecially on FB15k-237 where ConvKB gains sig- nificant improvements of 347 − 257 = 90 in MR (which is about 26% relative improvement) and ...CNN-based ... See full document
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Dependency based Convolutional Neural Networks for Sentence Embedding
... Convolutional neural networks (CNNs), originally invented in computer vision (LeCun et al., 1995), has recently attracted much attention in natural language processing (NLP) on problems such as sequence ... See full document
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Relation path feature embedding based convolutional neural network method for drug discovery
... methods, our method not only finds all candidate drugs but produces the best results. Additionally, we vary the settings of η to see how different percentage data affects the results. A set of scores are produced by a ... See full document
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End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion
... graph embedding has been an active research topic for knowledge base completion, with progressive im- provement from the initial TransE, TransH, DistMult et al to the current state-of-the-art ... See full document
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Foreign object debris material recognition based on convolutional neural networks
... a novel FOD material recognition approach based on both transfer learning and a mainstream deep convolutional neural network (D-CNN) ... See full document
10
Improving Neural Knowledge Base Completion with Cross Lingual Projections
... the neural tensor network model for knowledge base completion, proposed by Socher et ...multilingual embedding space obtained from monolingual word embeddings us- ing the ... See full document
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Towards End-to-End Acoustic Localization Using Deep Learning: From Audio Signal to Source Position Coordinates
... a novel approach for indoor acoustic source localization using microphone arrays and based on a Convolutional Neural Network ...our knowledge, the first published work in which ... See full document
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Commonsense Knowledge Base Completion
... sense knowledge by formulating the prob- lem as one of knowledge base comple- tion ...on knowledge bases like Freebase that re- late entities drawn from a fixed ...develop neural ... See full document
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Metal artifact reduction on cervical CT images by deep residual learning
... A novel RL- ARCNN is proposed to reduce metal artifacts in cervical CT ...proposed model is designed to predict residual images (the difference between artifact image and artifact-free image) rather than to ... See full document
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A MULTI CONTEXT EMBEDDING MODEL BASED ON CONVOLUTIONAL NEURAL NETWORK FOR TRAJECTORY DATA MINING
... social network by adopting various well-established measures of network proximity based on common neighbors or structure of paths connecting the users in who-calls-whom ... See full document
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LENA: Locality-Expanded Neural Embedding for Knowledge Base Completion
... state-of-the-art embedding models include, to the best of our knowledge, ProjE (Shi and Weninger 2017), DistMult (Yang et ...bedding model R-GCN(Schlichtkrull et ...the model to pool ... See full document
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A Capsule Network based Embedding Model for Knowledge Graph Completion and Search Personalization
... an embedding model, named CapsE, exploring a capsule net- work to model relationship triples (subject, re- lation, ...the embedding of an element in the ...for knowledge graph comple- ... See full document
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Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network
... CNN: convolutional neural network; CS-ResCNN: cost-sensitive residual convolutional neural network; ResCNN: native residual convolutional neural network; ... See full document
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PestNet : an end-to-end deep learning approach for large-scale multi-class pest detection and classification
... classification based on deep ...a novel module Channel-Spatial Attention (CSA) is proposed to be fused into Convolutional Neural Network (CNN) backbone for feature extraction and ... See full document
12
On Evaluating Embedding Models for Knowledge Base Completion
... all model pre- ...underestimate model performance due to un- observed true triples ranked high by the ...an embedding model is suitable for KBC only if it is feasible to determine high-scoring ... See full document
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Graph convolutional networks: a comprehensive review
... Each column of V is the eigenvector of L and σ (·) is the activation function. However, there are several issues with this convolutional structure. First, the eigenvector matrix V requires the explicit computation ... See full document
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Deep Convolution Neural Networks for Automatic Eyeglasses Removal
... approach based on PCA reconstruction by synthesizing eyeglasses and no eyeglasses facial images to remove eyeglasses on facial ...a novel visible information aided eyeglasses removing algorithm for thermal ... See full document
8
Glyph aware Embedding of Chinese Characters
... a novel glyph-aware embedding of Chi- nese ...of convolutional neural networks in computer vision, we use them to incorpo- rate the spatio-structural patterns of Chi- nese glyphs as rendered ... See full document
6
Automatic Musical Pattern Feature Extraction Using Convolutional Neural Network
... Figure 3: Convergence Curve in 200-epoch training Figure 3 shows the convergence of the training error rate of our CNN model, on four sub-datasets extracted from the GTZAN dataset. The smallest dataset contains 3 ... See full document
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A Position Encoding Convolutional Neural Network Based on Dependency Tree for Relation Classification
... the neural network pay more atten- tion to the crucial words and phrases in a ...our model since it is an important candidate clue to relation classifi- ... See full document
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