1 citations · 1 across the 4 of their papers we have counts for
4 papers
Dynamic technology impact analysis: A multi-task learning approach to patent citation prediction
Youngjin Seol, Jaewoong Choi, Seunghyun Lee +1
Machine learning (ML) models are valuable tools for analyzing the impact of technology using patent citation information. However, existing ML-based methods often struggle to accou…
Early screening of potential breakthrough technologies with enhanced interpretability: A patent-specific hierarchical attention network model
Jaewoong Choi, Janghyeok Yoon, Changyong Lee
Despite the usefulness of machine learning approaches for the early screening of potential breakthrough technologies, their practicality is often hindered by opaque models. To addr…
Design of reliable technology valuation model with calibrated machine learning of patent indicators
Seunghyun Lee, Janghyeok Yoon, Jaewoong Choi
Machine learning (ML) has revolutionized the digital transformation of technology valuation by predicting the value of patents with high accuracy. However, the lack of validation r…
Learning a Patent-Informed Biomedical Knowledge Graph Reveals Technological Potential of Drug Repositioning Candidates
Yongseung Jegal, Jaewoong Choi, Jiho Lee +3
Drug repositioning-a promising strategy for discovering new therapeutic uses for existing drugs-has been increasingly explored in the computational science literature using biomedi…