Results 51 to 60 of about 175,691 (261)

Geometry Interaction Knowledge Graph Embeddings

Proceedings of the AAAI Conference on Artificial Intelligence, 2022
Knowledge graph (KG) embeddings have shown great power in learning representations of entities and relations for link prediction tasks. Previous work usually embeds KGs into a single geometric space such as Euclidean space (zero curved), hyperbolic space (negatively curved) or hyperspherical space (positively curved) to maintain their specific ...
Cao, Zongsheng, Xu, Qianqian, Yang, Zhiyong, Cao, Xiaochun, Huang, Qingming   +4 more
openaire   +2 more sources

Convolutional Complex Knowledge Graph Embeddings [PDF]

, 2021
In this paper, we study the problem of learning continuous vector representations of knowledge graphs for predicting missing links. We present a new approach called ConEx, which infers missing links by leveraging the composition of a 2D convolution with a Hermitian inner product of complex-valued embedding vectors.
Demir, Caglar, Ngomo, Axel-Cyrille Ngonga   +1 more
openaire   +2 more sources

Distance Based Korean WordNet(alias. KorLex) Embedding Model

Applied Artificial Intelligence
The objective of this study was to create graph embedding vectors using Korean WordNet (KorLex) and apply them to neural network word-embedding models.
SeongReol Park, JoongMin Shin, Sanghyun Cho, Hyuk-Chul Kwon, Jung-Hun Lee   +4 more
doaj   +1 more source

End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

, 2018
Knowledge graph embedding has been an active research topic for knowledge base completion, with progressive improvement from the initial TransE, TransH, DistMult et al to the current state-of-the-art ConvE.
Bi, Jinbo, He, Xiaodong, Huang, Jing, Shang, Chao, Tang, Yun, Zhou, Bowen   +5 more
core   +1 more source

Modeling hepatic fibrosis in TP53 knockout iPSC‐derived human liver organoids

Molecular Oncology, EarlyView.
This study developed iPSC‐derived human liver organoids with TP53 gene knockout to model human liver fibrosis. These organoids showed elevated myofibroblast activation, early disease markers, and advanced fibrotic hallmarks. The use of profibrotic differentiation medium further amplified the fibrotic signature seen in the organoids.
Mustafa Karabicici, Soheil Akbari, Ceyda Caliskan, Canan Celiker, Ozden Oz, Leman Binokay, Gökhan Karakulah, Serif Senturk, Esra Erdal   +8 more
wiley   +1 more source

Predicting biomedical relationships using the knowledge and graph embedding cascade model.

PLoS ONE, 2019
Advances in machine learning and deep learning methods, together with the increasing availability of large-scale pharmacological, genomic, and chemical datasets, have created opportunities for identifying potentially useful relationships within ...
Xiaomin Liang, Daifeng Li, Min Song, Andrew Madden, Ying Ding, Yi Bu   +5 more
doaj   +1 more source

Improving FMEA Comprehensibility via Common-Sense Knowledge Graph Completion Techniques

IEEE Access, 2023
The Failure Mode Effect Analysis process (FMEA) is widely used in industry for risk assessment, as it effectively captures and documents domain-specific knowledge. This process is mainly concerned with causal domain knowledge.
Houssam Razouk, Xing Lan Liu, Roman Kern
doaj   +1 more source

Identification of serum protein biomarkers for pre‐cancerous lesions associated with pancreatic ductal adenocarcinoma

Molecular Oncology, EarlyView.
This work identified serum proteins associated with pancreatic epithelial neoplasms (PanINs) and early‐stage PDAC. Proteomics screens assessed genetically engineered mice with abundant PanINs, KPC mice (Lox‐STOP‐Lox‐KrasG12D/+ Lox‐STOP‐Lox‐Trp53R172H/+ Pdx1‐Cre) before PDAC development and also early‐stage PDAC patients (n = 31), compared to benign ...
Hannah Mearns, Jaclyn S. Long, Sergio Lilla, Kelly Hodge, Marcus J. G. W. Ladds, Colin Nixon, Paula Fernández‐Palanca, Sara Zanivan, Pilar Acedo, Stephen P. Pereira, Kevin M. Ryan   +10 more
wiley   +1 more source

Semantically Smooth Knowledge Graph Embedding [PDF]

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2015
This paper considers the problem of embedding Knowledge Graphs (KGs) consisting of entities and relations into lowdimensional vector spaces. Most of the existing methods perform this task based solely on observed facts. The only requirement is that the learned embeddings should be compatible within each individual fact. In this paper, aiming at further
Shu Guo, Quan Wang, Bin Wang, Lihong Wang, Li Guo   +4 more
openaire   +1 more source

Genetic attenuation of ALDH1A1 increases metastatic potential and aggressiveness in colorectal cancer

Molecular Oncology, EarlyView.
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova, Zuzana Kozovska, Ondrej Pos, Kristina Pavlov, Sachin Gulati, Peter Makovicky, Kristina Jakic, Monika Burikova, Eva Sedlackova, Barbora Svitkova, Silvia Tyciakova, Vojtech Bystry, Nicolas Blavet, Boris Tichy, Matej Hrnciar, Jaroslav Budis, Miroslav Tomas, Peter Dubovan, Georgina Kolnikova, Veronika Repaska, Nikoleta Mojzesova, Eva Zomborska, Daniel Pindak, Michal Mego, Tomas Szemes, Miroslava Matuskova   +25 more
wiley   +1 more source