Strikingness-Aware Evaluation for Temporal Knowledge Graph Reasoning

1. 1Propose a strikingness-aware evaluation framework for temporal knowledge graph reasoning
2. 2Identify and weight rare outstanding events that demand deeper reasoning
3. 3Implement a method to distinguish trivial repetitions from striking events
4. 4Evaluate the performance of TKGR models using the strikingness-aware framework
5. 5Compare the results with traditional evaluation methods to assess the improvement

Data scientists and AI researchers working on temporal knowledge graph reasoning can benefit from this framework to improve the accuracy of their models

💡 Rare outstanding events in temporal knowledge graphs require deeper reasoning and should be emphasized in evaluation

🚀 Introducing strikingness-aware evaluation for temporal knowledge graph reasoning! 🤖