The Data Science Lab at Dong-A University aims to incorporate a knowledge graph into recommender systems. Our goal is to discover potential paths between users and items by exploring dynamic interlinks within an evolving knowledge graph. We apply various recommendation, analytics, and reasoning techniques to real-time processing of data streams and (quasi-)static datasets in areas such as air quality monitoring, smart energy monitoring, location intelligence, retail tech, carbon-aware-computing, massive online open courses, and more.
클라우드에서 거대 언어모델 대상 탄소 배출량 저감 솔루션을 통해 챌린지에서 예비창업자 부문에서 우수상 수상
효과적인 가상발전소 운영을 향한 신뢰도 기반 발전량 예측 보정 모듈과 고령자 디지털 문해력을 향상하기 위한 유튜브 강의영상 기반 학습 관리 플랫폼을 주제로 공모전 대거 수상
IEEE CLOUD 2024에서 "Carbon-Aware and Fault-Tolerant Migration of Deep Learning Workloads in the Geo-distributed Cloud" 논문 발표
한국멀티미디어학회 춘계학술발표대회 2024.
한국멀티미디어학회 춘계학술발표대회 2024.
About The process involves measuring the carbon emissions generated from deep learning training. If a server's training process produces high carbo...
A Study on the Location Analysis of Green Car Charging Station Using Bayesian Network
A undergraduate project on managing carbon emissions on campus.
