Overview
The ACM Symposium on Applied Computing (SAC) is set to take place in Brno, Czech Republic, from March 30 to April 3, 2020. This year’s symposium features a dedicated track on Data Streams, inviting researchers to contribute original and unpublished work related to the challenges and methodologies associated with big data streams and large-scale machine learning.
Background & Relevance
The field of big data has evolved rapidly, presenting new challenges due to the increasing complexity and volume of data generated continuously from various sources. These data streams, which include information from the Internet of Things (IoT), smart cities, and healthcare devices, require innovative approaches for processing and analysis. Understanding and managing these streams is crucial for leveraging real-time data in various applications, making this track particularly relevant for researchers and practitioners in the AI and machine learning communities.
Key Details
- Event: ACM Symposium on Applied Computing (SAC) 2020
- Location: Brno, Czech Republic
- Dates: March 30 – April 3, 2020
- Submission Deadline: September 15, 2019
- Author Notification: November 10, 2019
- Camera-Ready Copies Due: November 25, 2019
- Track Link: Data Streams Track
- Main Symposium Link: ACM SAC 2020
Eligibility & Participation
This call for papers is open to researchers and practitioners working in the field of data streams and big data analytics. Contributions are welcomed from individuals and teams who can provide insights into algorithms, methods, and applications that address the challenges posed by data streams.
Submission or Application Guidelines
To submit a paper, authors should adhere to the following guidelines:
– Papers must be submitted in PDF format.
– All submissions should follow the ACM 2-column camera-ready format for inclusion in the symposium proceedings.
– The review process will be double-blind, meaning that authors must not include their names or affiliations in the submitted papers.
– Each paper must include the identification number provided by the eCMS system upon registration.
– The maximum length for final papers is 6 pages.
– For formatting templates, visit ACM Templates.
Additional Context / Real-World Relevance
The significance of data streams in today’s digital landscape cannot be overstated. As data continues to flow from various sources at unprecedented rates, the ability to analyze and derive insights from this data in real-time is essential. This track will foster discussions on innovative solutions and methodologies that can be applied across diverse domains, including urban computing and IoT applications.
Conclusion
Researchers are encouraged to submit their contributions to the Data Streams Track at ACM SAC 2020. This is an excellent opportunity to showcase your work and engage with leading experts in the field. Explore the submission guidelines and prepare your papers to contribute to the ongoing dialogue in big data and machine learning.
Category: CFP & Deadlines
Tags: big data, data streams, machine learning, real-time analytics, acm sac, data mining, iot, urban computing
