Results 241 to 250 of about 353,222 (280)

Curriculum Innovation: Neurocritical Care EEG Rounds: A Model to Improve Neurology Resident EEG Interpretation. [PDF]

Neurol Educ
Sanchez Mas ES, Powell ML, Malaga M, Goldsmith CE, Damani R, Lin L.   +5 more
europepmc   +1 more source

Symbolic rule-based knowledge graph completion

openaire   +1 more source

Some of the next articles are maybe not open access.

Related searches:

MRGAT: Multi-Relational Graph Attention Network for knowledge graph completion

Neural Networks, 2022
One of the most effective ways to solve the problem of knowledge graph completion is embedding-based models. Graph neural networks (GNNs) are popular and promising embedding models which can exploit and use the structural information of neighbors in knowledge graphs.
Xi-Zhao Wang, xiaoying zou
exaly   +3 more sources

XLNet For Knowledge Graph Completion

2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM), 2021
As the one of databases in artificial intelligence systems, knowledge graph has been widely used nowadays. Although the number of entities in current knowledge graphs has reached tens of millions or even billions level, directed cyclic graphs of their relations and entities composition were still relatively sparse.
Jie Liu, Xitong Ning, Wansong Zhang
openaire   +1 more source

Knowledge Graph Completion via Complete Attention between Knowledge Graph and Entity Descriptions

Proceedings of the 3rd International Conference on Computer Science and Application Engineering, 2019
The objective of learning representation of knowledge graph is assumed to encode both entities and relations into a continuous low-dimensional vector space. Previous methods usually represent the same entity in different triples with the same representation.
Minjun Zhao, Yawei Zhao, Bing Xu
openaire   +1 more source

Advanced Topic: Knowledge Graph Completion

2019
With the possible exception of good data collection and ontology design, information extraction and entity resolution are the two most important data-driven steps in a domain-specific knowledge graph construction pipeline. Yet, it is very rarely the case that the story ends there.
openaire   +1 more source