International Conference on Machine Learning and Big Data in IT Service Management
(ICMLBDITSM-27)

This track focuses on the latest developments in machine learning algorithms that enhance data processing capabilities. Researchers are invited to present innovative approaches that improve predictive analytics in IT service management.

This session explores the role of big data analytics in optimizing IT service management processes. Contributions should highlight case studies and frameworks that demonstrate effective data integration and analysis.

This track examines the implementation of intelligent systems in managing IT infrastructure. Papers should address the integration of AI algorithms to enhance system performance and automation.

This session focuses on the intersection of cloud computing and big data technologies. Authors are encouraged to discuss scalable solutions that leverage cloud resources for enhanced data analytics.

This track delves into methodologies for performance monitoring and optimization in IT services. Submissions should present novel techniques that utilize machine learning for real-time performance enhancement.

This session invites papers on innovative data processing frameworks tailored for IT service management. Contributions should emphasize efficiency and effectiveness in handling large datasets.