Proposing Machine Learning Models Suitable for Predicting Open Data Utilization DOI Open Access

Junyoung Jeong,

K. Cho

Published: June 19, 2024

As the digital transformation accelerates in our society, open data is being increasingly recognized as a key resource for innovation public sector. This study explores following two research questions: 1) Can machine learning approach be appropriately used measuring and evaluating utilization? 2) Should different models applied utilization depending on attributes (field usage type)? single-model (Random Forest, XGBoost, LightGBM, CatBoost) multi-model (Stacking Ensemble) methods. A finding that best-performing differed type of use). The applicability advance was also confirmed. contributes to application its intrinsic value society.

Language: Английский

Proposing Machine Learning Models Suitable for Predicting Open Data Utilization DOI Open Access

Junyoung Jeong,

K. Cho

Published: June 19, 2024

As the digital transformation accelerates in our society, open data is being increasingly recognized as a key resource for innovation public sector. This study explores following two research questions: 1) Can machine learning approach be appropriately used measuring and evaluating utilization? 2) Should different models applied utilization depending on attributes (field usage type)? single-model (Random Forest, XGBoost, LightGBM, CatBoost) multi-model (Stacking Ensemble) methods. A finding that best-performing differed type of use). The applicability advance was also confirmed. contributes to application its intrinsic value society.

Language: Английский

Citations

1