A Text-based Approach For Link Prediction on Wikipedia Articles
This is an incremental improvement for researchers in network analysis and link prediction, focusing on a specific competition dataset.
The paper tackled link prediction on Wikipedia articles using traditional machine learning models with POS tag features, achieving an F1 score of 0.99999 and placing 7th in the DSAA 2023 Challenge.
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