Invitation to Submit
제출 안내
The International Conference on Scalable Machine Learning for Big Data in IT , organized by the Korean Society for Academic Advancement (KSAA), invites original and high-quality research contributions from researchers, academicians, and professionals across all disciplines. Submissions are accepted in the form of research papers, case studies, and review articles aligned with the conference themes and academic focus areas.
International Conference on Scalable Machine Learning for Big Data in IT , 한국학술진흥학회(KSAA)가 주최하는 본 학술대회는 다양한 분야의 연구자, 학자 및 전문가들로부터 우수한 연구 논문을 모집합니다. 논문, 사례 연구 및 리뷰 논문 등 학술대회 주제에 부합하는 연구 결과를 제출할 수 있습니다.
Research Papers
연구 논문
Case Studies
사례 연구
Review Articles
리뷰 논문
Research Areas
연구 분야
Scalable Machine Learning Algorithms
Big Data Challenges In Scalability
Distributed Machine Learning Techniques
Real-time Big Data Processing Frameworks
Machine Learning For Large Datasets
Big Data Analytics For It Scalability
Cloud Computing And Machine Learning Integration
Scalable Architectures For Data Processing
Machine Learning For Resource Optimization
Big Data In Edge Computing Environments
Applications Of Big Data In Iot
Machine Learning For Performance Tuning
Big Data Storage Solutions For Scalability
Federated Learning For Big Data Applications
Scalable Data Pipelines For Ml
Machine Learning For Network Optimization
Big Data Visualization For Scalability
Machine Learning For Operational Analytics
Big Data Governance In Scalable Systems
Future Trends In Scalable Machine Learning
Review & Acceptance
심사 및 채택
All submissions will undergo a peer review process. Accepted papers may be presented at the conference and considered for further academic dissemination.
모든 제출 논문은 동료 심사 과정을 거치며, 채택된 논문은 학술대회 발표 및 추가 학술 확산의 기회를 갖게 됩니다.