[PDF] Top 20 A Translation Based Knowledge Graph Embedding Preserving Logical Property of Relations
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A Translation Based Knowledge Graph Embedding Preserving Logical Property of Relations
... novel translation-based knowledge graph embedding that preserves the logical properties of relations such as tran- sitivity and ...The embedding space generated by ... See full document
10
A Capsule Network based Embedding Model for Knowledge Graph Completion and Search Personalization
... for knowledge graphs compared to ...this property from images may be only right for the 1-1 relations, but not for the 1-M, M- 1 and M-M relations in the KGs because of the high variant of ... See full document
10
Jointly Embedding Knowledge Graphs and Logical Rules
... and relations into a continu- ous vector space, by using neural network architec- tures (Socher et ...models relations as translating op- erations, achieves a good trade-off between predic- tion accuracy ... See full document
11
TransGate: Knowledge Graph Embedding with Shared Gate Structure
... learning based methods which encode KGs into low- dimensional vector ...as translation between the heads and tails. We denote embedding vector with the same letters in ...the embedding h is ... See full document
8
Knowledge Graph Embedding with Numeric Attributes of Entities
... Knowledge Graph (KG) embedding projects entities and relations into low dimensional vector space, which has been successfully applied in KG completion ...previous embedding approaches ... See full document
5
Mining Event-Oriented Topics in Microblog Stream with Unsupervised Multi-View Hierarchical Embedding
... distribution- based event-oriented ...their relations is also an open-ended ...or graph-based models simply interpret relations in symbols, while incapable of providing continuous ... See full document
29
Transition-based Knowledge Graph Embedding with Relational Mapping Properties
... Many knowledge repositories nowadays con- tain billions of triplets, ...directed graph with enti- ties as nodes and relationships as ...the knowledge to enhance other intelligence- acquired ... See full document
10
Knowledge graph embedding by dynamic translation
... In this paper, we only combine our DT principle with classical translation-based models. One of our future works is to incorporate more information such as the relation paths [31], [32] and the textual ... See full document
10
Knowledge Graph Embedding via Dynamic Mapping Matrix
... as translation in the embedding ...the embedding h is close to the embedding t by adding the embedding r, that is h + r ≈ ...1-to-1 relations, but has flaws when dealing with ... See full document
10
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 2012; ... See full document
8
Zero shot Word Sense Disambiguation using Sense Definition Embeddings
... While knowledge-based approaches offer a way to disambiguate rare and unseen words into po- tentially rare senses, supervised methods consis- tently outperform these methods in the general set- ting where ... See full document
12
Improving Knowledge Graph Embedding Using Simple Constraints
... of knowledge graph em- bedding has been presented and quickly become a hot research ...and relations) into a continuous vector space, so as to simplify manipulation while preserving the ... See full document
12
Jointly Embedding Relations and Mentions for Knowledge Population
... and knowledge-based ...the relations, but the other side conducts relation in- ference depending on the local connecting pattern- s between entity pairs learnt from the knowledge graph ... See full document
6
Graph Based Translation Via Graph Segmentation
... machine translation (SMT) starts from sequence-based ...phrase- based (PB) translation model (Koehn et ...extending translation units from single words to ...learn translation ... See full document
11
Graph Based Translation Memory for Neural Machine Translation
... subsets based on the averaged similarity of each sentence in the retrieved trans- lation ...the translation memory indeed brings improvements of translation quality over all similarity ... See full document
8
Retrieving Sequential Information for Non Autoregressive Neural Machine Translation
... its translation ability while preserving the fast-decoding ...method based on a novel reinforcement algorithm for NAT (Reinforce-NAT) to reduce the variance and stabilize the training ...three ... See full document
12
Integration of Knowledge Graph Embedding Into Topic Modeling with Hierarchical Dirichlet Process
... domain knowledge is an effective strategy for enhancing the quality of inferred low-dimensional representations of documents by topic ...with knowledge graph em- bedding (TMKGE), a Bayesian ... See full document
11
Spectral Graph Based Method of Multimodal Word Embedding
... word embedding, multimodal versions of word2vec (Mikolov et ...word embedding methods based on a recurrent neural network to learn word vectors from their newly proposed large scale image caption ... See full document
6
SRDF: Extracting Lexical Knowledge Graph for Preserving Sentence Meaning
... cal knowledge graph from unstructured ...and knowledge representation in reified triple ...web, knowledge is commonly expressed in RDF triple form that consists of subject, predicate and ... See full document
5
Context Aware Graph Segmentation for Graph Based Translation
... The well-known phrase-based statistical transla- tion model (Koehn et al., 2003) extends the basic translation units from single words to continuous phrases to capture local phenomena. However, one of its ... See full document
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