Sign Up to like & get
recommendations!
0
Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3004448
Abstract: Knowledge graphs (KGs) play an important role in many real-world applications like information retrieval, question answering, relation extraction, etc. To reveal implicit knowledge from a knowledge graph (KG), viz. knowledge graph completion (KGC), is a…
read more here.
Keywords:
knowledge graph;
graph completion;
hamming distance;
knowledge ... See more keywords
Photo from wikipedia
Sign Up to like & get
recommendations!
2
Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3030076
Abstract: Knowledge graph completion (KGC) is a hot topic in knowledge graph construction and related applications, which aims to complete the structure of knowledge graph by predicting the missing entities or relationships in knowledge graph and…
read more here.
Keywords:
graph completion;
model;
graph;
knowledge graph ... See more keywords
Sign Up to like & get
recommendations!
2
Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3044343
Abstract: Graph neural networks have been proven to be very effective for representation learning of knowledge graphs. Recent methods such as SACN and CompGCN, have achieved the most advanced results in knowledge graph completion. However, previous…
read more here.
Keywords:
knowledge graph;
graph attention;
graph completion;
graph ... See more keywords
Photo from wikipedia
Sign Up to like & get
recommendations!
1
Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3113329
Abstract: The knowledge graph completion (KGC) task aims to predict missing links in knowledge graphs. Recently, several KGC models based on translational distance or semantic matching methods have been proposed and have achieved meaningful results. However,…
read more here.
Keywords:
entity;
language model;
knowledge graph;
graph completion ... See more keywords
Photo from wikipedia
Sign Up to like & get
recommendations!
1
Published in 2021 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2020.2970044
Abstract: Knowledge graphs (KG) often encounter knowledge incompleteness. The path reasoning that predicts the unknown path relation between pairwise entities based on existing facts is one of the most promising approaches to the knowledge graph completion.…
read more here.
Keywords:
graph completion;
knowledge graph;
entity;
relation ... See more keywords
Photo from wikipedia
Sign Up to like & get
recommendations!
1
Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3201562
Abstract: Despite incomplete multiview clustering (IMC) being widely studied in the past decade, it is still difficult to model the correlation among multiple views due to the absence of partial views. Most existing works for IMC…
read more here.
Keywords:
graph completion;
representation learning;
representation;
graph ... See more keywords
Photo from wikipedia
Sign Up to like & get
recommendations!
1
Published in 2021 at "Frontiers in Neurorobotics"
DOI: 10.3389/fnbot.2021.674428
Abstract: With the rapid development of artificial intelligence, Cybernetics, and other High-tech subject technology, robots have been made and used in increasing fields. And studies on robots have attracted growing research interests from different communities. The…
read more here.
Keywords:
knowledge;
encoder decoder;
graph completion;
knowledge graph ... See more keywords
Photo from wikipedia
Sign Up to like & get
recommendations!
2
Published in 2022 at "Entropy"
DOI: 10.3390/e24101495
Abstract: Knowledge graph completion is an important technology for supplementing knowledge graphs and improving data quality. However, the existing knowledge graph completion methods ignore the features of triple relations, and the introduced entity description texts are…
read more here.
Keywords:
knowledge;
graph completion;
knowledge graph;
multi task ... See more keywords