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18 results with keyword: 'frs simple knowledge graph embedding model entity prediction'

FRS: A Simple Knowledge Graph Embedding Model for Entity Prediction

However, the importance of feature processing for the triple data is overlooked. Feature processing is mainly used to enhance the interaction between triples, i.e., entities

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2021
Neighborhood Mixture Model for Knowledge Base Completion

Keywords: Knowledge base completion, embedding model, mixture model, link prediction, triple classification, entity pre- diction, relation prediction..

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2020
Improving Knowledge Graph Embedding Using Simple Constraints

Finally, we combine together the basic embedding model of ComplEx, the non-negativity constraints on entity representations, and the approximate en- tailment constraints over

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2020
Semi supervised Entity Alignment via Joint Knowledge Embedding Model and Cross graph Model

Early en- tity alignment approaches either rely on human efforts ( Mahdisoltani et al. Recent embed- ding approaches show significant improvement on entity alignment. We

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2020
Knowledge Graph Embedding for Ecotoxicological Effect Prediction

In this paper we present a preliminary study of the benefits of using Semantic Web tools to integrate different data sources and knowledge graph embedding approaches to improve

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2019
A Review of the Remaining Import Restrictions

Liberalization is redundant for this group, although price ratios have gone further down, and imports increased for two out of six items which were deregulated after 1985 and

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2021
Graph Pattern Entity Ranking Model for Knowledge Graph Completion

GRank is easy to interpret because outputs are described by GPARs, unlike knowledge graph embedding mod- els, and so efficient that it outperformed the state- of-the-art knowledge

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10
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2020
Case Id: 0993d72f-a100-4bb7-862d-dfc55b7b69f1

If your organisation is acting both as a professional association and as the competent authority dealing with the recognition of professional qualifications, please fill in only

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2021
TransG : A Generative Model for Knowledge Graph Embedding

In this paper, we propose a generative Bayesian non-parametric infinite mixture embedding model, TransG, to address a new issue, multiple relation semantics, which can be commonly

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2020
PREDICT TB : Prevention of Resistance, Evaluation of Diagnostics and Intensified or Custom-made Treatment of Tuberculosis

Regarding the cytokine expression, the IFn-γ concentrations in lung homogenates and serum which in untreated mice remained at a stable level until 30 weeks after

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2021
A Contactless Electromagnetic Coupling Resonance-Based Volume Fraction Detection Technique for Gas-Liquid Flow

The variation of equivalent resistance and inductance against the volume fraction are investigated for the stratified flow and annular flow.. Besides, the relationship between the

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2020
Enzyme That Is Used During Rna Transcription

Helix is that the enzyme used during rna transcription factors which needs to a process called the replication at the protein factors which needs to begin to.. Website in dna are

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2021
DYNAPAC CM 13 SPARE PARTS CATALOGUE SCM013-2EN1

Para evitar errores al pedir repuestos utilicen las etiquetas abajo descritas para identificar los catálogos en la parte trasera de la carpeta.. En la etiqueta se ven los números

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2021
On Evaluating Embedding Models for Knowledge Base Completion

We argue that the entity ranking protocol, which is currently used to evaluate knowledge graph embedding models, is not suitable to answer this question since only a subset of the

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2020
Running head: LEARNING BENEFITS OF EXPLANATION 1

Our studies had three objectives: (a) to differentiate effects of explanation from those due to observation (Study 1) or verbalization (Study 2), (b) to examine whether and how

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2021
Opposite Variability of Indonesian Throughflow and South China Sea Throughflow in the Sulawesi Sea

The South China Sea Throughflow (SCSTF) involves inflow of the Kuroshio into the South China Sea (SCS) through the Luzon Strait and outflow into the Indonesian seas through two

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2021
1Introduction Abstract { aihuang,zxy-dcs } @tsinghua.edu.cn StateKeyLab.ofIntelligentTechnologyandSystems,NationalLab.forInformationScienceandTechnology,Dept.ofComputerScienceandTechnology,TsinghuaUniversity,Beijing100084,PRChinabookman@vip.163.com; HanXi

As precise link prediction is criti- cal for knowledge graph embedding, we propose a manifold-based embedding principle (ManifoldE) which could be treated as a well-posed

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2022
Semantically Smooth Knowledge Graph Embedding

In this paper, we have proposed a novel approach to KG embedding, referred to as Semantically S- mooth Embedding (SSE). The key idea of SSE is to impose constraints on the

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2020

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