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2024
Journal
Explainable Product Classification for Customs
E. Lee, S. Kim, S. Kim, S. Jung, H. Kim, and M. Cha
ACM 2024 [Transactions on Intelligent Systems and Technology]
2023
Conference
Transformer as a hippocampal memory consolidation model based on NMDAR-inspired nonlinearity
D.-K. Kim, J. Kwon, M. Cha*, and C. Justin Lee*
NeurlPS 2023 [proc. Advances in Neural Information Processing Systems]
SlackedFace: Learning a Slacked Margin for Low-Resolution Face Recognition
C.-Y. Low, J. C.-L. Chai, J. Park, K. Ann, and M. Cha*
BMVC 2023 [proc. of the British Machine Vision Conference]
Towards Attack-tolerant Federated Learning via Critical Parameter Analysis
S. Han, S. Park, F. Wu, S. Kim, B. Zhu, X. Xie, and M. Cha
ICCV 2023 [proc. of the International Conference on Computer Vision]
GraphFC: Customs Fraud Detection with Label Scarcity
K. Singh, Y.-C. Tsai, C.-T. Li, M. Cha, and S.-D. Lin
CIKM 2023 [proc. of the ACM Conference on Information and Knowledge Management]
A Comparative Study of Reference Reliability in Multiple Language Editions of Wikipedia
A. Baigutanova, D. Saez-Trumper, M. Redi, M. Cha, and P. Aragon
CIKM 2023 [proc. of the ACM Conference on Information and Knowledge Management]
Fine-Grained Socioeconomic Prediction from Satellite Images with Distributional Adjustment
D. Ahn, M. Song, S. Lee, Y. Choi, J. Kim, S. Park, H. Yang and M. Cha
CIKM 2023 [proc. of the ACM Conference on Information and Knowledge Management]
Machine Learning Driven Aid Classification for Sustainable Development
J. Lee, H. Song, D. Lee, S. Kim, J. Sim, M. Cha, K.-R.Park
IJCAI 2023 [International Joint Conference on Artificial Intelligence]
FedDefender: Client-Side Attack-Tolerant Federated Learning
S. Park, S. Han, F. Wu, S. Kim, B.B. Zhu, X. Xie and M. Cha
KDD 2023 [ACM SIGKDD Conference on Knowledge Discovery and Data Mining]
Customs Import Declaration Datasets
C. Jeong, S. Kim, J. Park, and Y. Choi
KDD 2023 workshop [ACM SIGKDD, workshop on Machine Learning in Finance]
SQuARe: A Large-Scale Dataset of Sensitive Questions and Acceptable Responses Created Through Human-Machine Collaboration
H. Lee, S. Hong, J. Park, T. Kim, M. Cha, Y. Choi, B. Kim, G. Kim, E.-J. Lee, Y. Lim, A. Oh, S. Park, J.-W. Ha
ACL 2023 [Annual Meeting of the Association for Computational Linguistics]
Who Should Pay When Machines Cause Harm? Laypeople’s Expectations of Legal Damages for Machine-Caused Harm
G. Lima, N. Grgic-Hlaca, J.K. Jeong and M. Cha
FAccT 2023 [ACM Conference on Fairness, Accountability, and Transparency]
Recognizability Embedding Enhancement for Very Low-Resolution Face Recognition and Quality Estimation
C. Long, Tiong-Sik Ng, C-Y. Low, J. Park, and A. Teoh
CVPR 2023 [IEEE Conference on Computer Vision and Pattern Recognition]
Unified Neural Topic Model via Contrastive Learning and Term Weighting
S. Han, M. Shin, S. Park, C. Jung, M. Cha
EACL 2023 [Conference of the European Chapter of the Association for Computational Linguistics]
Detecting Contextomized Quotes in News Headlines by Contrastive Learning
S. Song, H. Song, K. Park, J. Han, M. Cha
EACL 2023 [Conference of the European Chapter of the Association for Computational Linguistics]
Blaming Humans and Machines: What Shapes People’s Reaction to Algorithmic Harm
G. Lima, N. Grgic-Hlaca, M. Cha
CHI 2023 [Conference on Human Factors in Computing Systems]
Longitudinal Assessment of Reference Quality on Wikipedia
A. Baigutanova, J. Myung, A.-J. Chou, D. Saez-Trumper, M. Redi, C. Jung, M. Cha
WWW 2023 [proc. of the ACM Web Conference]
DualFair: Fair Representation Learning at Both Group and Individual Levels via Contrastive Self-supervision
S. Han, S. Lee, F. Wu, S. Kim, C. Wu, X. Wang, X. Xie, M. Cha
WWW 2023 [proc. of the ACM Web Conference]
Neural Classification of Terrestrial Biomes
V. Shen, D. Kim, E. Zeller and M. Cha
BIGComp2023
Self-supervised learning for climate downscaling
K. Singh, C. Jeong, S. Park, A. Babur, E. Zeller and M. Cha
BIGComp2023
Journal
A Human-machine Collaborative Approach Measures Economic Development using Satellite Imagery
D. Ahn, J. Yang, M. Cha*, H. Yang*, J. Kim*, S. Park*, S. Han, E. Lee, S. Lee, and S. Park
Nature Communications 2023
The Potential of Chatbots for Emotional Support and Promoting Mental Well-Being in Different Cultures: Mixed Methods Study
H. Chin, H. Song, G. Baek, M. Shin, C. Jung, M. Cha, J. Choi and C. Cha
JMIR 2023 [In Journal of Medical Internet Research]
The Secret to Successful Evocative Messages: Anger Takes the Lead in Information Sharing Over Anxiety
J. Han,* S. E. Lee, M. Cha*
Communication Monographs 2023
Social dimensions impact individual sleep quantity and quality
S. Park, A. Zhunis, M. Constantinides, L. Aiello, D. Quercia, and M. Cha.
Scientific Reports 2023
Sensing Accident-Prone Features in Urban Scenes for Proactive Driving and Accident Prevention
S. Mishra, P. Rajendran, L. Vecchietti, D. Har
IEEE 2023 [Transactions on intelligent transportation systems]
Multidimensional entropic bound: Estimator of entropy production for Langevin dynamics with an arbitrary time-dependent protocol
S. Lee, D. Kim, J. Park, W. Kim, H. Park, and J. Lee.
Physical Review Research 2023
Multi-Stage Machine Learning Model for Hierarchical Tie Valence Prediction
K.Singh, S.Lee, G. Labianca, J. M. Fagan and M. Cha
ACM 2023 [Transactions on Knowledge Discovery from Data]
Active Learning for Human-in-the-Loop Customs Inspection
S. Kim, T. Mai, S. Han, S. Park, T. Nguyen, J. So, K. Singh and M. Cha
IEEE 2023 [Transactions on Knowledge and Data Engineering]
User-Chatbot Conversations During the COVID-19 Pandemic: A Study Based on Topic Modeling and Sentiment Analysis
H. Chin, G. Lima, M. Shin, A. Zhunis, C. Cha, J. Choi, and M. Cha
JMIR 2023 [In Journal of Medical Internet Research]
2022
Conference
Self-explaining deep models with logic rule reasoning
S. Lee, X. Wang, S. Han, X. Yi, X. Xie, M. Cha
NIPS 2022 [In NeurIPS 2022, November 2022]
Protein Sequence Design in a Latent Space via Model-based Reinforcement Learning
M. Lee, L. F. Vecchietti, H. Jung, H. Ro, M. Cha, H. M. Kim
NIPS 2022 workshop [Machine Learning in Structural Biology]
Transformer needs NMDA receptor nonlinearity for long-term memory
D. Kim, J. Kwon, M. Cha, C. J. Lee
NIPS 2022 workshop [Memory in Artificial and Real Intelligence (MemARI)]
Playgrounds for Abstraction and Reasoning
S. Kim, P. Phunyaphibarn, D. Ahn, S. Kim
NIPS 2022 workshop [Neuro Causal and Symbolic AI (nCSI)]
Others Are to Blame: A Multi-Faceted View on Whom People Consider Responsible For Online Misinformation
G. Lima, J. Han, M. Cha
CSCW 2022 [In Proceedings of the ACM on Human-Computer Interaction]
FedX: Unsupervised Federated Learning with Cross Knowledge Distillation
S Han, S Park, F Wu, S Kim, C Wu, X Xie, M Cha
ECCV 2022 [proc. of the 17th European Conference on Computer Vision]
Downscaling Earth System Models with Deep Learning
S Park, K Singh, A Nellikkattil, E Zeller, TD Mai, M Cha
KDD 2022 [proc. of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining]
The Conflict Between Explainable and Accountable Decision-Making Algorithms
G. Lima, N. Grgić-Hlača, J.K. Jeong, M. Cha
FAccT 2022 [ACM Conference on Fairness, Accountability, and Transparency]
Emotion Bubbles: Emotional Composition of Online Discourse Before and After the COVID-19 Outbreak
A. Zhunis, G Lima, H. Song, J. Han, M. Cha
WWW 2022 [proc. of the ACM Web Conference]
Using Web Data to Reveal 22-Year History of Sneaker Designs
S. Park, H. Song, S. Han, L. Manovich, B. Weldegebriel, E. Arielli, M. Cha
WWW 2022 [proc. of the ACM Web Conference] : Best Paper Candidate
Learning economic indicators by aggregating multi-level geospatial information
S. Park, S. Han, D. Ahn, J. Kim, J. Yang, S. Lee, S. Hong, J. Kim, S. Park, and M. Cha
AAAI 2022 [In proc. of the AAAI Conference on Artificial Intelligence]
Knowledge Sharing via Domain Adaptation in Customs Fraud Detection
S. Park, S. Kim, and M. Cha
AAAI 2022 [In proc. of the AAAI Conference on Artificial Intelligence]
How XAI May Be Exploited To Create Seemingly Blameworthy AI
G. Lima, N. Grgić-Hlača, M. Cha, J. K. Jeong
CHI 2022 Workshop [Human-Centered Explainable AI (HCXAI)]
Journal
Responses to COVID-19 with probabilistic programming
A. Zhunis, T.-D. Mai, S. Kim
Frontiers in Public Health 2022
A Systematic Mapping Study and Empirical Comparison of Data-Driven Intrusion Detection Techniques in Industrial Control Networks
B. A. Tama, S. Y. Lee, & S. Lee
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING 2022
Revisiting Gradient Boosting-Based Approaches for Learning Imbalanced Data: A Case of Anomaly Detection on Power Grids
M. H. L. Louk, and B. A. Tama.
Big Data and Cognitive Computing 2022
Disaster assessment using computer vision and satellite imagery: Applications in water-related building damage detection
D Kim, J Won, E Lee, K Park, J Kim, S Park, H Yang, M Cha
Frontiers 2022 [Frontiers in Environmental Science]
Understanding the Categories and Characteristics of Depressive Moods in Chatbot Data (ko: 챗봇 데이터에 나타난 우울 담론의 범주와 특성의 이해)
H. Chin, C. Jung, G. Baek, C. Cha, J. Choi, and M. Cha
KIPS Transactions on Software and Data Engineering 2022
An improved semantic segmentation with region proposal network for cardiac defect interpretation
S. Nurmaini, B. A. Tama, M. N. Rachmatullah, A. Darmawahyuni, A. I. Sapitri, F. Firdaus, B. Tutuko.
Neural Computing and Applications 2022
Inferring dissipation maps from videos using convolutional neural networks
Y. Bae, D. Kim, and H. Jeong
Physical Review Research 2022
An Implicit Identity-Extended Data Augmentation for Low-Resolution Face Representation Learning
C.Y. Low, and A. Beng-Jin Teoh
IEEE Transactions on Information Forensics and Security 2022
Voices that Care Differently: Understanding the Effectiveness of a Conversational Agent with an Alternative Empathy Orientation and Emotional Expressivity in Mitigating Verbal Abuse
H. Chin, and M. Yi
International Journal of Human- Computer Interaction 2022
Effects of Child Maltreatment on Physical Activity and Sleep in Healthy Adults: A Wearable Device Use Experiment (ko: 건강한 성인에서 아동기 학대 경험이 신체 활동과 수면에 미치는 영향: 웨어러블 디바이스 사용 실험)
M.-S. Kim, S. Park, M. Cha, and S.-W.
Journal of the Korean Society of Biological Therapies in Psychiatry 2022
Exploring Text Summarization for Fake News Detection
J. Bian, S. Lee, K. Singh, and M. Cha
In Journal of KIISE 2022
News Comment Sections and Online Echo Chambers: The Ideological Alignment Between Partisan News Stories and Their User Comments
J. Han, Y. Lee, J, Kim, and M. Cha
Journalism, March 2022
Misinformation, Believability, and Vaccine Acceptance Over 40 Countries: Takeaways From the Initial Phase of The COVID-19 Infodemic
K. Singh, G. Lima, M. Cha, C. Cha, J. Kulshrestha, Y. Ahn, O. Varol
Plos One 2022
QAnon Shifts Into the Mainstream, Remains a Far-Right Ally
S. Zihiri, G. Lima, J. Han, M. Cha, W. Lee
Heliyon 2022
Active Learning for Human-in-the-Loop Customs Inspection
S. Kim, T. Mai, S. Han, S. Park, T. Nguyen, J. So, K. Singh, M. Cha
IEEE Transactions on Knowledge and Data Engineering (TKDE) 2022
Understanding and identifying the use of emotes in toxic chat on Twitch
J. Kim, D. Wohn, and M. Cha
Online Social Networks and Media 2022
2021
Customs Fraud Detection in the Presence of Concept Drift
T. Mai, K. Hoang, A. Baigutanova, G. Alina, and S. Kim [Workshop on Incremental Classification and Clustering, Concept Drift, Novelty Detection in Big/Fast Data Context in conjunction with IEEE International Conference on Data Mining, December 2021]
Elsa: Energy-based Learning for Semi-supervised Anomaly Detection
S. Han, H. Song, S. Lee, S. Park, and M. Cha [British Machine Vision Conference, November 2021]
The Conflict Between People’s Urge to Punish AI and Legal Systems
G. Lima, M. Cha, C. Jeon, and K.S. Park [In Frontiers in Robots and AI, November 2021]
On the Social-Relational Moral Standing of AI: An Empirical Study Using AI-Generated Art
G. Lima, A. Zhunis, L. Manovich, and M. Cha [In Frontiers in Robots and AI, August 2021]
Analyzing Biases in Perception of Truth in NewsStories and Their Implications for Fact Checking
M. Babaei, A. Chakraborty, J. Kulshrestha, E.M. Redmiles, M. Cha, and K. Gummadi [In IEEE Transactions on Computational Social Systems, Accepted for publication, July 2021. (SCIE, IF=5.36)]
Finding Epic Moments in Live Content through Learning from Collective Decisions
H. Song, K. Park and M. Cha [In EPJ Data Science, Accepted for publication, 2021]
COVID-19 Vaccine Acceptance in the US and UK in the Early Phase of the Pandemic: AI-Generated Vaccines Hesitancy for Minors, and the Role of Governments
G. Lima, M. Cha, C. Cha, and H. Hwang [In Journal of the Korean Data Analysis Socie, 23(3), 1045–1064, June 2021] [PDF]
Urban green space and happiness in developed countries
O.-H. Kwon, I. Hong, J. Yang, D.Y. Wohn, W.-S. Jung, and M. Cha [In EPJ Data Science, 2021]
— Related News
Urban green space affects citizens’ happiness
Science Daily
Urban green space brings happiness when money can’t buy it anymore
Phys.org
Disruption in Chinese E-Commerce During COVID-19
Y. Yuan, M. Guan, Z. Zhou, S. Kim, M. Cha, D. Jin, and Y. Li [In Frontiers in Computer Science, 2021]
Prevalence of Misinformation and Factchecks on the COVID-19 Pandemic in 35 Countries: Observational Infodemiology Study
M. Cha, C. Cha, K. Singh, G. Lima, Y.-Y. Ahn, J. Kulshrestha, and O. Varol [In JMIR Human Factors, 8(1), January 2021]
The Medium and the Backlash: The Disparagement of the MeToo Movement in Online Public Discourse in South Korea
S.Y. Bae, T. Kim, Yu-i Ha, and M. Cha [In International Journal of Communication, 15, 768–791, January 2021. (IF=1.28)]
COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication
S. Park, S. Han, J. Kim, M. M. Molaie, H. D. Vu, K. Singh, J. Han, W. Lee, and M. Cha [In Journal of Medical Internet Research (JMIR), 2021. doi:10.2196/23272. Impact Factor = 5.03 [SCIE]]
An Experimental Study to Understand User Experience and Perception Bias Occurred by Fact-checking Messages
S. Park, J. Y. Park, H. Chin, J. Kang, and M. Cha [In proc. of the Web Conference (WWW), April 2021. Acceptance rate for full paper = 20.6%] [PDF]
Improving Unsupervised Image Clustering With Robust Learning
S. Park, S. Han, S. Kim, D. Kim, S. Park, S. Hong, and M. Cha [In proc. of the 2021 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021] [Github]
The Presence of Unexpected Biases in Online Fact-checking
S. Park, J.Y. Park, J.-H. Kang, and M. Cha [In Harvard Kennedy School (HKS) Misinformation Review, 2020]
Learning to Detect Incongruence in News Headline and Body Text via a Graph Neural Network
S. Yoon, K. Park, M. Lee, T. Kim, M. Cha, and K. Jung [IEEE Access, To appear in 2021. (SCIE, IF=3.764)]
Automatically Detecting Image-Text Mismatch on Instagram with Deep Learning
Y. Ha, K. Park, S.J. Kim, J. Joo, and M. Cha [In Journal of Advertising, January 2021. (SSCI, IF=6.302)]
Human Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Making
G. Lima, N. G.-H., and M. Cha [In proc. of the ACM CHI Conference on Human Factors in Computing Systems, 2021]
Designing a Mobile Intervention Platform to Help Alleviate Insomnia Symptoms in College Students (대학생의 불면 증상 완화를 위한 모바일 중재 플랫폼 개발 연구)
박성규, 이상원, 안동현, 차미영 [Journal of the Korean Society of Biological Therapies in Psychiatry, Vol 27, No 1, 2021] [PDF]
Neural Embedding of Sneaker Designs over 23 Years
박성규, 송현호, 한성원, Lev Manovich, Emanuele Arielli, and 차미영 [한국정보과학회 KCC, June 2021]
쇼핑몰 상품 카테고리 분류를 위한 Hyperbolic Interaction Model의 적용과 분석
김시현, 이은지, 박성원, 김선동, 차미영 [한국정보과학회 KCC, June 2021]
뉴스 요약문을 기반으로 한 가짜 뉴스 탐지
J. Bian, S. Lee, K. Singh, and M. Cha [한국정보과학회 KCC, June 2021]
위키백과를 이용한 COVID-19 범유행 정보 구조 분석
김단우, 이다민, 명재현, 정창욱, 홍인호, Diego Sáez-Trumper, 윤진혁, 정우성, 차미영 [한국정보과학회 KCC, June 2021]
2020
A Comprehensive and Adversarial Approach to Unsupervised Embedding Learning
Y.-Z. Hsu, S. Han, S. Park, M. Cha, and C.-T. Li [In proc. of the IEEE International Conference on Big Data, 2020 (Acceptance Rate=15.5%)]
Anger contributes to the spread of COVID-19 misinformation
J. Han, M. Cha, and W. Lee [In Harvard Kennedy School (HKS) Misinformation Review, 2020]
Collecting the Public Perception of AI and Robot Rights
G. Lima, C. Kim, S. Ruy, C. Jeon, M. Cha [In proc. of the ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), 2020]
Mitigating Embedding and Class Assignment Mismatch in Unsupervised Image Classification
S. Han, S. Park, S. Park, S. Kim, M. Cha [In proc. of the European Conference on Computer Vision (ECCV), August 2020]
Explaining the Punishment Gap of AI and Robots
K. Park, G. Lima, M. Cha, and C. Jeon [In proc. of the We Robot (International Conference on Law and Policy Relating to Robotics), August 2020]
From Anticipation to Action: Data Reveal Mobile Shopping Patterns During a Yearly Mega Sale Event in China
M. Guan, M. Cha, Y. Wang, J. Sun, and Y. Li., [Transactions on Knowledge and Data Engineering, June 2020. (SCI, IF=5.876)]
DATE: Dual Attentive Tree-aware Embedding for Customs Fraud Detection
S. Kim, Y.-C. Tsai, K. Singh, Y. Choi, E. Ibok, C.-T. Li, and M. Cha [In proc. of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020 (Acceptance Rate=16%)]
Learning to Score Economic Development from Satellite Imagery
S. Han, D. Ahn, S. Park, J. Yang, S. Lee, J. Kim, H. Yang, S. Park, and M. Cha [In proc. of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020 (Acceptance Rate=16%)]
Detecting Fake News in Social Media: An Asia-Pacific Perspective
M. Cha, W. Gao, and C.-T. Li [In Communications of the ACM (CACM) Big Trends, Vol 63, No 4, 68–71, 2020]
“Trust me, I have a Ph.D.”: A Propensity Score Analysis on the Halo Effect of Disclosing One’s Offline Social Status in Online Communities
K. Park, H. Kwak, H. Song, and M. Cha [In proc. of the International AAAI Conference on Weblogs and Social Media (ICWSM), 2020]
Lightweight and Robust Representation of Economic Scales from Satellite Imagery
S. Han, D. Ahn, H. Cha, J. Yang, S. Park, and M. Cha [In proc. of the AAAI Conference on Artificial Intelligence (AAAI), 2020]
Learning How Spectator Reactions Affect Popularity on Twitch
J. Kim, K. Park, H. Song, J.Y. Park, and M. Cha [In proc. of the IEEE Conference on Big Data and Smart Computing (BigComp), 2020]
Green Space and Happiness of Developed Countries
F. Hashemi, A. Behrouz, J. Yang, D.Y. Wohn, and M. Cha [In proc. of the IEEE Conference on Big Data and Smart Computing (BigComp), 2020. (Short Paper)]
Disruption in the Chinese E-Commerce During COVID-19
Y. Yuan, G. Muzhi, Z. Zhou, S. Kim, M. Cha, D. Jin, Y. Li [arXiv:2009.14605]
Carpe Diem, Seize the Samples Uncertain at the Moment for Adaptive Batch Selection
H. Song, M. Kim, S. Kim, J. Lee [In proc. of the ACM International Conference on Information and Knowledge Management (CIKM), 2020]
Ada-Boundary: Accelerating the DNN Training via Adaptive Boundary Batch Selection
H. Song, S. Kim, M. Kim, J. Lee [Machine Learning (SCI, IF=2.730, ECML-PKDD Journal track)]
Neural User Embedding From Browsing Events
M. An, S. Kim [In proc. of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2020]
Will Punishing Robots Become Imperative in the Future?
G. Lima, M. Cha, C. Jeon, and K. Park [In proc. of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020]
Responsible AI and Its Stakeholders
G. Lima, and M. Cha [In Fair & Responsible AI Workshop, co-located with the 2020 CHI Conference on Human Factors in Computing Systems, 2020]
Revisit Prediction by Deep Survival Analysis
S. Kim, H. Song, S. Kim, B. Kim, J. Lee [In proc. of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2020, Singapore]
BaitWatcher: A lightweight web interface for the detection of incongruent news headlines
K. Park, T. Kim, S. Yoon, M. Cha, and K. Jung [In Fake News, Disinformation, and Misinformation in Social Media-Emerging Research Challenges and Opportunities. Springer, 2020]
QoS-Based Zero-Rating of Cellular Applications
Ramneek, P. Hosein, S. Pack, and K. Singh [In proc. of the International Conference on Information Networking (ICOIN), January 2020]
A Risk Communication Event Detection Model via Contrastive Learning
M. Shin, S. Han, S. Park, M. Cha [In proc. of the 3rd NLP4IF Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda – COLING workshop, 2020]
Human-in-the-loop solution for scoring economic development from geospatial data
S. Park, D. Ahn, S. Han, E. Lee, D. Kim, J. Yang, S. Lee, S. Park, H. Yang, J. Kim, M. Cha [HAMLETS (Human And Machine in-the-Loop Evaluation and Learning Strategies) – NeurIPS workshop, 2020]
Teaching Machines to Measure Economic Activities from Satellite Images: Challenges and Solutions
D. Ahn, M. Cha, S. Han, J. Kim, S. Lee, S. Park, S. Park, H. Yang, J. Yang [Banca d’Italia and Federal Reserve Board Joint Conference on Nontraditional Data & Statistical Learning with Applications to Macroeconomics (BIFRBConf), 2020]
Descriptive AI Ethics: Collecting and Understanding the Public Opinion
G. Lima, and M. Cha [Ethics in Design Workshop, ACM CSCW 2020]
DPESS: Daytime Satellite Imagery-based Prediction of Demographic Attributes Using Embedding Spatial Statistics (DPESS: 임베딩 공간 통계를 이용한 주간 위성영상 기반의 인구 통계학적 속성 예측)
H. Cha, S. Han, D. Ahn, S. Park, and M. Cha [In Journal of KIISE, 742-747, August 2020]
2019
Clustering Insomnia Patterns by Data from Wearable Devices: Algorithm Development and Validation Study
S. Park, S.-W. Lee, S. Han, M. Cha [In JMIR mHealth and uHealth (JMU), Vol 7, No 12, December 2019, e14473 (SCI-E, IF=4.3)]
Predicting New Adopters via Socially-Aware Neural Graph Collaborative Filtering
Y.-C. Tsai, M. Guan, C.-T. Li, M. Cha, Y. Li, and Y. Wang [In International Conference on Computational Data and Social Networks (CSoNet), 2019]
Learning Sleep Quality from Daily Logs
S. Park, C-T. Li, S. Han, C. Hsu, S.W. Lee, and M. Cha [In proc. of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), August 4–8, 2019, Anchorage, AK, USA (Acceptance Rate=14%)]
Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder
S. Yoon, K. Park, J. Shin, H. Lim, S. Won, M. Cha, K. Jung [In proc. of the AAAI Conference on Artificial Intelligence (AAAI), 2019. (Acceptance Rate=16%)]
Understanding Facebook News Posts Comment Reading and Reacting Behavior through Political Extremism and Cultural Orientation
M.Y. Almoqbel, D.Y. Wohn, R.A. Hayes, M. Cha [In Elsevier Computers in Human Behavior Vol 100, 118-126, November 2019 (SCI-E, IF=4.306)]
Analyzing Biases in Perception of Truth in News Stories and their Implications for Fact Checking
M. Babaei, A. Chakraborty, J. Kulshrestha, E.M. Redmiles, M. Cha, and K. Gummadi [In proc. of the ACM Conference on Fairness, Accountability, and Transparency (FAT*), 2019]
Predicting Time-Bounded Purchases During a Mega Shopping Festival
M. Guan, M. Cha, Y. Li, Y. Wang, and J. Yu [In proc. of the IEEE International Conference on Big Data and Smart Computing (BigComp), 2019]
Image Super Resolution Techniques Applied on Satellite Imagery
C. Phentmunee, H. Doan Thi, H. Dieu Vu, D. Ahn, H.Cha, S. Han, and M. Cha [In International Workshop and Challenge on Real-World Recognition from Low-Quality Images and Videos, co-located with ICCV, 2019]
Predicting Urbanization from Daytime Satellite Imagery based on Descriptive Statistics
D. Ahn, S. Han, H.Cha and M. Cha [In Workshop on AI and the United Nation SDGs, co-located with IJCAI, 2019]
The Fallacy of Echo Chambers: Analyzing the Political Slants of User-Generated News Comments in Korean Media
J. Han, Y. Lee, J. Lee, and M. Cha [In proc. of the 5th Workshop on Noisy User-generated Text (W-NUT 2019), co-located with EMNLP, 2019]
DPESS: Daytime Satellite Imagery-based Prediction of Demographic Attributes Using Embedding Spatial Statistics (DPESS: 임베딩 공간 통계를 이용한 주간 위성영상 기반의 인구 통계학적 속성 예측)
차현지, 한성원, 안동현, 박성원, 차미영 [한국정보과학회 KCC, 2019]
Detection of hate speech with emoticons using Twitch tv online streaming chat data (트위치 온라인 스트리밍 채팅 데이터를 이용한 이모티콘이 포함된 혐오 표현 탐지)
최영일, 김재헌, 차미영, 원동희 [한국정보과학회 KCC, 2019]
Predicting Demographics from Satellite Imagery based on Convolutional Neural Network and Transfer Learning (위성사진과 CNN 기반 전이 학습을 통한 인구 통계 예측)
박성원, 안동현, 차현지, 한성원, 차미영 [한국정보과학회 KCC, 2019]
Deep learning based classification of the quotation types embedded in economic news headlines (딥러닝 기반 모델을 활용한 국내 경제뉴스 제목 내 인용 형태 분류 및 뉴스의 의견성 분석)
이영인, 김정욱, 한지영, 김태균, 하유이, 차미영 [한국정보과학회 KCC, 2019]
Highlight Prediction on Online Streaming Video (온라인 스트리밍 동영상 인기 구간 예측)
송현호, 김정민, 박건우, 차미영 [한국정보과학회 KCC, 2019]
Robots for Class President: Children’s Positions Toward AI Robot Rights (로봇을 반장으로: AI 로봇 권리에 대한 어린이의 입장 연구)
G. Lima, S. Park, and M. Cha [한국정보과학회 KCC, 2019]