Seungmin Jin

According to our database, Seungmin Jin authored at least 11 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

ContextRAG: Extraction-Free Hierarchical Graph Construction for Retrieval-Augmented Generation.

Roman Prosvirnin, Sergei Kuznetsov, Seungmin Jin

CoRR, May, 2026

RSD: A Local Triangulation Audit Primitive for Learned Vector Blocks.

Seungmin Jin

CoRR, May, 2026

2025

From Patterns to Predictions: A Shapelet-Based Framework for Directional Forecasting in Noisy Financial Markets.

Juwon Kim, Hyunwook Lee, Hyotaek Jeon, Seungmin Jin, Sungahn Ko

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

2023

A Visual Analytics System for Improving Attention-based Traffic Forecasting Models.

Seungmin Jin, Hyunwook Lee, Cheonbok Park, Hyeshin Chu, Yunwon Tae, Jaegul Choo, Sungahn Ko

IEEE Trans. Vis. Comput. Graph., 2023

2022

A Graphical Workflow Exploration Environment For Visual Analytics.

Chunggi Lee, Juyoung Oh, Seungmin Jin, Isaac Cho, Sungahn Ko

CoRR, 2022

Learning to Remember Patterns: Pattern Matching Memory Networks for Traffic Forecasting.

Hyunwook Lee, Seungmin Jin, Hyeshin Chu, Hongkyu Lim, Sungahn Ko

Proceedings of the Tenth International Conference on Learning Representations, 2022

An Empirical Study on How People Perceive AI-generated Music.

Hyeshin Chu, Joohee Kim, Seongouk Kim, Hongkyu Lim, Hyunwook Lee, Seungmin Jin, Jongeun Lee, Taehwan Kim, Sungahn Ko

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

An Empirical Experiment on Deep Learning Models for Predicting Traffic Data.

Hyunwook Lee, Cheonbok Park, Seungmin Jin, Hyeshin Chu, Jaegul Choo, Sungahn Ko

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

2020

A Visual Analytics System for Exploring, Monitoring, and Forecasting Road Traffic Congestion.

Chunggi Lee, Yeonjun Kim, Seungmin Jin, Dongmin Kim, Ross Maciejewski, David S. Ebert, Sungahn Ko

IEEE Trans. Vis. Comput. Graph., 2020

ST-GRAT: A Novel Spatio-temporal Graph Attention Networks for Accurately Forecasting Dynamically Changing Road Speed.

Cheonbok Park, Chunggi Lee, Hyojin Bahng, Yunwon Tae, Seungmin Jin, Kihwan Kim, Sungahn Ko, Jaegul Choo

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

STGRAT: A Spatio-Temporal Graph Attention Network for Traffic Forecasting.

Cheonbok Park, Chunggi Lee, Hyojin Bahng, Taeyun won, Kihwan Kim, Seungmin Jin, Sungahn Ko, Jaegul Choo

CoRR, 2019