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Lim, Sunghoon (임성훈)

Department: Department of Industrial Engineering(산업공학과)

Website: http://sunghoonlim.unist.ac.kr

Lab: Unstructured Data Mining and Machine Learning Lab. (비정형 데이터마이닝 및 기계학습 연구실)

Research Keywords: 기계학습, 인공지능, 비정형데이터마이닝, Artificial Intelligence (AI), Unstructured Data Mining, Machine Learning

Research Interests: Research at Unstructured Data Mining and Machine Learning Laboratory"Development of machine learning models for effective knowledge discovery from unstructured data" TopicsMachine Learning / Deep Learning(Unstructured) Data MiningIndustrial Artificial Intelligence (AI+X)Text MiningSocial Network Analysis / CrowdsourcingApplicationsSafety Management (e.g., Car Crash Detection)Manufacturing (e.g., Predictive Maintenance, Anomaly Detection, 3D Printing)Customer Feedback Analysis Using Online Data (e.g., Social Media, Online Customer Reviews, Recommender Systems)Healthcare (e.g., Disease Discovery)etc.

This table browses all dspace content
Issue Date	Title	Author(s)	Type	View	Altmetrics
2021-12	A deep learning-based time series model with missing value handling techniques to predict various types of liquid cargo traffic	Lim, Sunghoon; Kim, Sun Jun; Park, YoungJae, et al	ARTICLE	11	A deep learning-based time series model with missing value handling techniques to predict various types of liquid cargo traffic
2021-12	DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction	Tuarob, Suppawong; Wettayakorn, Poom; Phetchai, Ponpat, et al	ARTICLE	9	DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction
2021-11	Car crash detection using ensemble deep learning and multimodal data from dashboard cameras	Choi, Jae Gyeong; Kong, Chan Woo; Kim, Gyeongho, et al	ARTICLE	24	Car crash detection using ensemble deep learning and multimodal data from dashboard cameras
2021-02	A Stacking-Based Deep Neural Network Approach for Effective Network Anomaly Detection	Tama, Bayu Adhi; Lim, Sunghoon	ARTICLE	189	A Stacking-Based Deep Neural Network Approach for Effective Network Anomaly Detection
2021-02	Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation	Tama, Bayu Adhi; Lim, Sunghoon	ARTICLE	91	Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation
2020-10	A Comparative Performance Evaluation of Classification Algorithms for Clinical Decision Support Systems	Tama, Bayu Adhi; Lim, Sunghoon	ARTICLE	171	A Comparative Performance Evaluation of Classification Algorithms for Clinical Decision Support Systems
2020-05	A Multi-Objective Differential Evolutionary Method for Constrained Crowd Judgment Analysis	Chatterjee, Sujoy; Lim, Sunghoon	ARTICLE	350	A Multi-Objective Differential Evolutionary Method for Constrained Crowd Judgment Analysis
2020-03	인공지능 기반의 자동차사고 감지 시스템 적용 사례 분석	최재경; 공찬우; 임성훈	ARTICLE	25	인공지능 기반의 자동차사고 감지 시스템 적용 사례 분석
2019-09	Mining Twitter data for causal links between tweets and real-world outcomes	Lim, Sunghoon; Tucker, Conrad S.	ARTICLE	423	Mining Twitter data for causal links between tweets and real-world outcomes
2018-09	A semantic network model for measuring engagement and performance in online learning platforms	Lim, Sunghoon; Tucker, Conrad S.; Jablokow, Kathryn, et al	ARTICLE	577	A semantic network model for measuring engagement and performance in online learning platforms
2018-06	Automated Discovery of Product Feature Inferences Within Large-Scale Implicit Social Media Data	Tuarob, Suppawong; Lim, Sunghoon; Tucker, Conrad S.	ARTICLE	511	Automated Discovery of Product Feature Inferences Within Large-Scale Implicit Social Media Data
2017-11	Mitigating Online Product Rating Biases Through the Discovery of Optimistic, Pessimistic, and Realistic Reviewers	Lim, Sunghoon; Tucker, Conrad S.	ARTICLE	558	Mitigating Online Product Rating Biases Through the Discovery of Optimistic, Pessimistic, and Realistic Reviewers
2017-02	An unsupervised machine learning model for discovering latent infectious diseases using social media data	Lim, Sunghoon; Tucker, Conrad S.; Kumara, Soundar	ARTICLE	501	An unsupervised machine learning model for discovering latent infectious diseases using social media data
2016-06	A Bayesian Sampling Method for Product Feature Extraction From Large-Scale Textual Data	Lim, Sunghoon; Tucker, Conrad S.	ARTICLE	508	A Bayesian Sampling Method for Product Feature Extraction From Large-Scale Textual Data
2011-12	Optimizing Zone-dependent Two-level Facility Location Problem	Lim, Sunghoon; Sung, Chang-Sup; Song, Sang Hwa	ARTICLE	496

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