Results 21 to 30 of about 9,217,308 (160)

TBRm: A Time Representation Method for Industrial Knowledge Graph

Applied Sciences, 2022
With the development of the artificial intelligence industry, Knowledge Graph (KG), as a concise and intuitive data presentation form, has received extensive attention and research from both academia and industry in recent years.
Keyan Cao, Chuang Zheng
doaj   +1 more source

Conflict-aware multilingual knowledge graph completion

, 2023
Knowledge graph completion (KGC), a task that aims at predicting missing links with existing information inside a knowledge graph (KG), has emerged as a popular research area in recent years. While many existing works have demonstrated effectiveness on a
Zhang, Weihang, Sun, Jiahao, Ovidiu Şerban, Guo, Yike, Serban, Ovidiu, Yike Guo, Jiahao Sun, Weihang Zhang   +7 more
core   +1 more source

Optimal temporal planning using the plangraph framework [PDF]

, 2007
The past few years have seen a rapid development in AI Planning and Scheduling. Many algorithms and techniques have been studied and improved to deal with more complex and difficult planning domains.
Dinh, Tien Ba
core   +4 more sources

Search to Pass Messages for Temporal Knowledge Graph Completion

Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Completing missing facts is a fundamental task for temporal knowledge graphs (TKGs). Recently, graph neural network (GNN) based methods, which can simultaneously explore topological and temporal information, have become the state-of-the-art (SOTA) to complete TKGs.
Zhen Wang 0004, Haotong Du, Quanming Yao, Xuelong Li 0001   +3 more
openaire   +2 more sources

Towards a Maude tool for model checking temporal graph properties [PDF]

, 2011
We present our prototypical tool for the verification of graph transformation systems. The major novelty of our tool is that it provides a model checker for temporal graph properties based on counterpart semantics for quantified m-calculi.
Lluch-Lafuente, Alberto, Luch Lafuente A, Vandin, Andrea, Lafuente, Alberto Lluch, Vandin A   +4 more
core   +1 more source

Temporal Knowledge Graph Completion using a Linear Temporal Regularizer and Multivector Embeddings

, 2021
S.2569-2578Representation learning approaches for knowledge graphs have been mostly designed for static data. However, many knowledge graphs involve evolving data, e.g., the fact (The President of the United States is Barack Obama) is valid only from ...
Yung-Yu Chen, Mojtaba Nayyeri, Chen, Yung-Yu, Jens Lehmann, Xu, Chengjin, Nayyeri, Mojtaba, Lehmann, Jens, Chengjin Xu   +7 more
core   +1 more source

JOINT FEATURES-BASED KNOWLEDGE GRAPH COMPLETION [PDF]

International Journal of Intelligent Computing and Information Sciences
Knowledge graphs (KGs) help in resolving data inconsistencies and redundancies by organizing information in a unified structure, paving the way for building scalable, interpretable AI systems, as they provide a transparent way to trace reasoning paths ...
Maha Farghaly, Mostafa Aref, Mahmoud Mounir   +2 more
doaj   +1 more source

Enabling inductive knowledge graph completion via structure-aware attention network

, 2023
: Knowledge graph completion (KGC) aims at complementing missing entities and relations in a knowledge graph (KG). Popular KGC approaches based on KG embedding are typically limited to the transductive setting, i.e., all entities must be seen during ...
Jin, Qun, Qun Jin, Liu, Wei, Wang, Can, Weimin Li, Li, Weimin, Jingchao Wang, Wei Liu, Wang, Jingchao, Can Wang   +9 more
core   +1 more source

Learning Sequence Encoders for Temporal Knowledge Graph Completion [PDF]

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018
Research on link prediction in knowledge graphs has mainly focused on static multi-relational data. In this work we consider temporal knowledge graphs where relations between entities may only hold for a time interval or a specific point in time. In line with previous work on static knowledge graphs, we propose to address this problem by learning ...
Alberto García-Durán, Sebastijan Dumancic, Mathias Niepert   +2 more
openaire   +4 more sources

Hyperplane-based time-aware knowledge graph embedding for temporal knowledge graph completion

Journal of Intelligent & Fuzzy Systems, 2022
Knowledge Graph (KG) embedding approaches have been proved effective to infer new facts for a KG based on the existing ones–a problem known as KG completion. However, most of them have focused on static KGs, in fact, relational facts in KGs often show temporal dynamics, e.g., the fact (US, has president, Barack Obama, [2009–2017]) is only valid from ...
Peng He, Gang Zhou, Hongbo Liu, Yi Xia, Ling Wang   +4 more
openaire   +2 more sources