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History repeats itself: A Baseline for Temporal Knowledge Graph Forecasting
April 26, 2024, 4:42 a.m. | Julia Gastinger, Christian Meilicke, Federico Errica, Timo Sztyler, Anett Schuelke, Heiner Stuckenschmidt
cs.LG updates on arXiv.org arxiv.org
Abstract: Temporal Knowledge Graph (TKG) Forecasting aims at predicting links in Knowledge Graphs for future timesteps based on a history of Knowledge Graphs. To this day, standardized evaluation protocols and rigorous comparison across TKG models are available, but the importance of simple baselines is often neglected in the evaluation, which prevents researchers from discerning actual and fictitious progress. We propose to close this gap by designing an intuitive baseline for TKG Forecasting based on predicting recurring …
abstract arxiv comparison cs.lg evaluation forecasting future graph graphs history importance knowledge knowledge graph knowledge graphs simple temporal type
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