[PDF] Top 20 Knowledge Graph Embedding with Numeric Attributes of Entities
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Knowledge Graph Embedding with Numeric Attributes of Entities
... Recently, a number of Knowledge Graphs (KGs) have been created, such as DBpe- dia (Lehmann, 2015), YAGO (Mahdisoltani et al., 2015), and Freebase (Bollacker et al., 2008). KGs encode structured informa- tion of ... See full document
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Knowledge Graph Embedding via Dynamic Mapping Matrix
... the entities in dictionary in turn for each triplet in test ...correct entities ranked in top 10 ...in knowledge graphs, the corrupted triplet should be regard as a correct ... See full document
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TransGate: Knowledge Graph Embedding with Shared Gate Structure
... A number of works attempt to improve knowledge graph embedding in different ways. Some models explore different loss function to improve embeddings. Zhou et al. (Zhou et al. 2017) propose a ... See full document
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Improving Knowledge Graph Embedding Using Simple Constraints
... Our work has some similarities to those which integrate logical background knowledge into KG embedding (Rockt¨aschel et al., 2015; Wang et al., 2015; Guo et al., 2016, 2018). Most of such works, however, ... See full document
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Improved Knowledge Graph Embedding Using Background Taxonomic Information
... In relational learning, embeddings for entities and rela- tionships are used to generalize from existing data. These embeddings are often formulated in terms of tensor factor- ization (Nickel, Tresp, and Kriegel ... See full document
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TransG : A Generative Model for Knowledge Graph Embedding
... Recently, knowledge graph embedding, which projects symbolic entities and rela- tions into continuous vector space, has be- come a new, hot topic in artificial intelli- ...our ... See full document
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Relation Embedding with Dihedral Group in Knowledge Graph
... incomplete knowledge graph (KG) in the downstream ...predictions, embedding methods try to learn low-rank representations for both entities and relations such that the bi- linear form defined ... See full document
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Transition-based Knowledge Graph Embedding with Relational Mapping Properties
... the entities, ...as entities locates on MANY-side will finally be trained extremely close to each other in the embedding space and also hard to be discrimi- ... See full document
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Integration of Knowledge Graph Embedding Into Topic Modeling with Hierarchical Dirichlet Process
... Knowledge graph (KG) embedding (Bordes et ...for entities and relations to preserve the inherent structure of ...and entities to have identical latent representa- tions, which is a ... See full document
11
Knowledge Graph Embedding for Ecotoxicological Effect Prediction
... NCBI entities to map to ECOTOX (we focus only on instances, ...its entities) covering all 929 mappings from the (incomplete) ground truth, thus, an estimated recall of ...TERA knowledge graph ... See full document
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A Translation Based Knowledge Graph Embedding Preserving Logical Property of Relations
... Knowledge graph embedding is another promi- nent method for link prediction (Bordes et ...embeds entities of a knowledge graph into a continuous low dimensional space as vectors, ... See full document
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Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding
... by a zero vector. The results are reported in Table 4. We ob- serve that although superior to MEAN, Global-Attention is outperformed by Query-Attention, demonstrating the neces- sity of query relation awareness. The ... See full document
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End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion
... Knowledge 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 ... See full document
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Context Dependent Knowledge Graph Embedding
... entities connected to a same node are usually im- plicitly related to each other, even if they are not directly connected. Figure 1 gives two examples. Shaquille O Neal and NBA in the former ex- ample and Nevada ... See full document
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Text-Based Joint Prediction of Numeric and Categorical Attributes of Entities in Knowledge Bases
... constructed knowledge bases play an important role in information systems, but are essentially always ...for Knowledge Base Completion, the task of predicting new attributes of entities given ... See full document
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Knowledge graph embedding by dynamic translation
... Recently, embedding-based approaches have shown strong feasibility and ...embed) entities and relations in knowledge graphs into a continuous, real-valued and low-dimensional vector space, and then ... See full document
10
Semantically Smooth Knowledge Graph Embedding
... of entities) and enforce the em- bedding space to be semantically smooth—entities belonging to the same semantic category should lie close to each other in the embedding ...(i.e. entities ... See full document
11
Representing Text for Joint Embedding of Text and Knowledge Bases
... of knowledge base and textual in- formation was first shown to outperform either source alone in the framework of path-ranking al- gorithms in a combined knowledge base and text graph (Lao et ... See full document
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GAKE: Graph Aware Knowledge Embedding
... These knowledge bases have benefited many applications, such as web search and question ...meanwhile, knowledge base embedding, which aims to learn a D-dimensional vector for each subject ...given ... See full document
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Tackling Long Tailed Relations and Uncommon Entities in Knowledge Graph Completion
... problem, Knowledge Graph Com- pletion (KGC) task is introduced to automatically deduce and fill the missing ...and embedding-based methods (Bordes et ...the entities within its facts are also ... See full document
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