Results 41 to 50 of about 8,905,265 (199)

Temporal Graph Analysis using Gradoop

, 2019
The temporal analysis of evolving graphs is an important requirement in many domains but hardly supported in current graph database and graph processing systems.
Thor, Andreas, Rost, Christopher, Rahm, Erhard   +2 more
core   +1 more source

Summarizing Entity Temporal Evolution in Knowledge Graphs [PDF]

Companion Proceedings of The 2019 World Wide Web Conference, 2019
Companion Proceedings of The 2019 World Wide Web Conference on - WWW '19 The 2019 World Wide Web Conference, WWW '19, San Francisco, USA, 13 May 2019 - 17 May 2019; New York, NY : ACM Press 961-965 (2019).
Mayesha Tasnim, Diego Collarana, Damien Graux, Fabrizio Orlandi, Maria-Esther Vidal   +4 more
openaire   +4 more sources

Selective Temporal Knowledge Graph Reasoning

Proceedings of the Language Resources and Evaluation Conference
Temporal Knowledge Graph (TKG), which characterizes temporally evolving facts in the form of (subject, relation, object, timestamp), has attracted much attention recently. TKG reasoning aims to predict future facts based on given historical ones. However, existing TKG reasoning models are unable to abstain from predictions they are uncertain, which ...
Zhongni Hou, Xiaolong Jin 0001, Zixuan Li 0001, Long Bai 0002, Jiafeng Guo, Xueqi Cheng   +5 more
openaire   +4 more sources

3DRTE: 3D Rotation Embedding in Temporal Knowledge Graph

IEEE Access, 2020
Temporal knowledge graph (TKG) embedding has received increasing attention in the academia. However, most existing methods are extensions of traditional translation models.
Jingbin Wang, Wang Zhang, Xinyuan Chen, Jing Lei, Xiaolian Lai   +4 more
doaj   +1 more source

Knowledge Graph

, 2018
This Wikipedia entry describes the Knowledge Graph as a knowledge base by Google. It enhances the search engine's results by gathering information from a variety of sources.
Wikipedia, HostingInstitution
core   +1 more source

STAGCN: Spatial–Temporal Attention Graph Convolution Network for Traffic Forecasting

Mathematics, 2022
Traffic forecasting plays an important role in intelligent transportation systems. However, the prediction task is highly challenging due to the mixture of global and local spatiotemporal dependencies involved in traffic data.
Yafeng Gu, Li Deng
doaj   +1 more source

Spatio-Temporal Graph Convolutional Network Incorporating Knowledge Graph Embeddings for Hydrological Time Series Prediction

IEEE Access
This paper proposes a spatio-temporal graph convolutional network incorporating knowledge graph embeddings for hydrological time series prediction. A knowledge graph is constructed to integrate the spatio-temporal features of hydrological monitoring ...
Xin Jin, Mengyuan Qin, Hao Duan
doaj   +1 more source

Temporal Graph Neural Networks for Modeling Student Knowledge Evolution and Predicting Learning Trajectories

Algorithms
Accurately modeling student knowledge evolution is a central challenge in personalized learning and adaptive educational systems. Traditional sequential or static approaches often fail to capture both the temporal dynamics of learning and the relational ...
Deborah Olaniyan, Ruth Wario
doaj   +1 more source

Multi-Granularity Temporal Knowledge Graph Question Answering Based on Data Augmentation and Convolutional Networks

Applied Sciences
The multi-granularity temporal knowledge graph question-answering model consists of two core tasks: question information extraction and knowledge graph embedding representation.
Yizhi Lu, Lei Su, Liping Wu, Di Jiang
doaj   +1 more source

One-shot Learning for Temporal Knowledge Graphs

CoRR, 2020
Most real-world knowledge graphs are characterized by a long-tail relation frequency distribution where a significant fraction of relations occurs only a handful of times. This observation has given rise to recent interest in low-shot learning methods that are able to generalize from only a few examples.
Mehrnoosh Mirtaheri, Mohammad Rostami, Xiang Ren 0001, Fred Morstatter, Aram Galstyan   +4 more
openaire   +2 more sources