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Jan 22, 2025 · A paper presented at LREC-COLING 2024 that proposes a method to model temporal dynamics and high-order interactions in TKG with dynamic hypergraph embedding. …

Nov 25, 2024 · This paper reviews existing methods for learning representations of temporal knowledge graphs (TKGs), which integrate time information into factual triples. It categorizes …

Aug 24, 2024 · Enter the Temporal Knowledge Graph (TKG), a powerful extension that incorporates temporal data, allowing for the modeling of how entities and relationships evolve …

Graphiti builds dynamic, temporally aware Knowledge Graphs that represent complex, evolving relationships between entities over time. Graphiti ingests both unstructured and structured …

Knowledge Graph (KG) reasoning that predicts missing facts for incomplete KGs has been widely explored. However, reasoning over Temporal KG (TKG) that predicts facts in the future is still …

To address this issue, this paper proposes a novel TKGQA model called GATQR, which integrates graph attention mechanism. The model utilizes a pre-trained temporal knowledge …

Jan 22, 2025 · TempValid conceptualizes confidence and other coefficients as learnable parameters to avoid inaccurate estimation and combinatorial explosion. Furthermore, we …

Nov 19, 2024 · In a world where data drives decisions, Temporal Knowledge Graphs (TKGs) are rapidly emerging as a game-changing tool. By incorporating the dimension of time into …

Sep 5, 2022 · Temporal knowledge graph (TKG) representation learning aims to project entities and relations in TKGs to a low-dimensional vector space while preserving the evolutionary …

The task also becomes more challenging on temporal knowledge graph. In this paper, we introduce some models on static knowledge graph and temporal knowledge graph, and …

This paper summarizes the recent advances in temporal knowledge graph completion (TKGC) research, which incorporates the temporal validity of facts to capture the dynamic evolution of …

Jan 16, 2022 · A paper that summarizes the recent advances in temporal knowledge graph completion (TKGC) research, a method that incorporates timestamps of facts to capture the …

3 days ago · Temporal knowledge graph (TKG) reasoning is a crucial task that has gained increasing research interest in recent years. Most existing methods focus on reasoning at past …

In the realm of temporal knowledge graph (TKG) extrapolation, subgraph-based reasoning methods offer clearer insights than those based on individual paths, effectively capturing local …

Nov 20, 2022 · Temporal knowledge graph, serving as an effective way to store and model dynamic relations, shows promising prospects in event forecasting.

Temporal knowledge graphs (TKGs) can store and model dynamic relational information. Recently, research on generative models has addressed the limitations of embedding methods …

4 days ago · Knowledge graphs can improve the performance of recommendation systems and provide explanations for recommendation results, which have been widely applied in the next …

Besides, such a meta temporal reasoning procedure goes beyond existing meta-learning paradigms on static knowledge graphs that fail to handle temporal adaptation with large entity …

2 days ago · AbstractIn the dynamic landscape of social network analysis, the accurate prediction of implicit relationships presents a pivotal challenge. This paper introduces an innovative …

2 days ago · However, in some circumstances, implemented RAG techniques using a knowledge graph can yield more accurate results than a vector graph. That raises the question of how to …

Jun 20, 2024 · Recently, the evolving dynamics of knowledge have attracted a growing interest in Temporal Knowledge Graph Question Answering (TKGQA), an emerging task to answer …

1 day ago · Temporal Knowledge Graph (TKG) reasoning seeks to predict future incomplete facts leveraging historical data.

Students’ knowledge mastery, learning ability, and question difficulty all influence the performance metrics of knowledge tracing. This paper proposes a deep knowledge tracing model that …

1 day ago · Ever since the introduction of the Google Knowledge Graph, a growing number of organizations have adopted this powerful technology to drive efficiency and effectiveness in …

5 hours ago · Background Accurate and timely monitoring of influenza prevalence is essential for effective healthcare interventions. This study proposes a graph neural network (GNN)-based …

Jan 21, 2025 · Dynamic graph representation learning plays a crucial role in understanding evolving behaviors. However, existing methods often struggle with flexibility, adaptability, and …