A Text-based Approach For Link Prediction on Wikipedia Articles

TL;DR

This paper explores a text-based machine learning approach using POS tags to predict links between Wikipedia articles, achieving high accuracy and competitive ranking in a challenge.

Contribution

It introduces a novel application of POS tag features with traditional ML models for Wikipedia link prediction, demonstrating competitive performance.

Findings

F1 score of 0.99999 achieved

Ranked 7th in DSAA 2023 Challenge

Source code publicly available

Abstract

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