arXiv:2309.00317
공식 코드 · Papers with Code
A Text-based Approach For Link Prediction on Wikipedia Articles
원문 초록
This paper present our work in the DSAA 2023 Challenge about Link Prediction for Wikipedia Articles. We use traditional machine learning models with POS tags (part-of-speech tags) features extracted from text to train the classification model for predicting whether two nodes has the link. Then, we use these tags to test on various machine learning models. We obtained the results by F1 score at 0.99999 and got 7th place in the competition. Our source code is publicly available at this link: https://github.com/Tam1032/DSAA2023-Challenge-Link-prediction-DS-UIT_SAT
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Demystifying Distributed Training of Graph Neural Networks for Link Prediction
Learnable Spatial-Temporal Positional Encoding for Link Prediction
Future Link Prediction Without Memory or Aggregation
Understanding Generalization in Node and Link Prediction
A PID-Controlled Tensor Wheel Decomposition Model for Dynamic Link Prediction
Open-World Social Event Classification
토론
이 논문과 연결된 포럼 글이 아직 없습니다.