Overview
The ACM Symposium on Applied Computing (SAC) is a renowned global event for professionals in applied computing fields. The upcoming 2026 edition will feature a dedicated Data Streams (DS) track, sponsored by AI-BOOST, aimed at fostering discussions and innovations in data stream processing. This track is significant as it addresses the challenges posed by the rapid growth of data generated from various sources, including IoT and smart cities.
Background & Relevance
Data stream processing is a critical area within the broader field of big data and machine learning. With the increasing volume and complexity of data generated continuously, efficient processing techniques are essential. Researchers are exploring new algorithms and adapting existing methods to handle the unique characteristics of data streams, such as their high-speed flow and non-stationary distributions. This track will serve as a platform for sharing insights and advancements in this vital research area.
Key Details
- Paper Submission Deadline: September 26, 2025
- Author Notification: October 31, 2025
- Camera-Ready Copy Deadline: December 5, 2025
- Submission Portal: SAC 2026 Webpage
- Topics of Interest:
- Real-Time Analytics
- Data Stream Models
- Big Data Mining
- Large-Scale Machine Learning
- Languages for Stream Query
- Continuous Queries
- Clustering from Data Streams
- Decision Trees from Data Streams
- Association Rules from Data Streams
- Bayesian Networks from Data Streams
- Visualization Techniques for Data Streams
- Incremental Online Learning Algorithms
- Temporal, Spatial, and Spatio-Temporal Data Mining
- Scalable Algorithms
- Real-Time Applications using Stream Data
- Social Network Stream Mining
- Urban Computing, Smart Cities
- Internet of Things (IoT)
Eligibility & Participation
This call for papers is open to researchers and practitioners working on data streams and related fields. It targets those who are developing innovative solutions or methodologies to address the challenges associated with big data streams.
Submission or Application Guidelines
Authors are encouraged to submit original and unpublished papers. The following guidelines must be adhered to:
– Submissions should follow the ACM 2-column camera-ready format.
– The paper length is limited to 8 pages, with an option for 2 additional pages for an extra charge.
– A double-blind review process will be employed; therefore, author names must not be included in the submitted papers.
– All papers must include the identification number provided by the eCMS system upon registration.
– Papers should be submitted in PDF format via the SAC 2026 Webpage.
More Information
The Data Streams track at SAC 2026 is positioned within a growing body of research that emphasizes the importance of effective data processing techniques in an era dominated by big data. The insights gained from this track will contribute to the ongoing evolution of methodologies in machine learning and data analytics, making it a crucial event for researchers in these domains.
Conclusion
Researchers are encouraged to submit their contributions to the Data Streams track at ACM SAC 2026. This is an excellent opportunity to share your work with a global audience and engage with leading experts in the field. Explore the submission guidelines and prepare your papers for this significant event.
Category: CFP & Deadlines
Tags: data streams, big data, machine learning, real-time analytics, data mining, acm sac, smart cities, internet of things, distributed stream mining, urban computing
