For the past thirty years, the ACM Symposium on Applied Computing has been a primary gathering forum for applied computer scientists, computer engineers, software engineers, and application developers from around the world.

SAC 2024 is sponsored by the ACM Special Interest Group on Applied Computing,

The goal of DS track is to promote a meeting point and a discussion forum for researchers interested in any aspect of Data Stream processing.

Important Dates

1. Paper Submission: October 13, 2023
2. Author Notification: November 17, 2023
3. Camera-ready Copy: December 15, 2023

Motivation

The rapid growth in Big Data information science and technology in general and the complexity and volume of data in particular have introduced new challenges for the research community. Many sources produce data continuously. Examples include the Internet of Things (IoT), Smart Cities, Urban Computing, sensor networks, wireless networks, radio frequency identification (RFID), customer click streams, telephone records, multimedia data, scientific data, sets of retail chain transactions, etc. These sources are called data streams. A data stream is an ordered sequence of instances that can be read only once or a small number of times using limited computing and storage capabilities. These sources of data are characterized by being open-ended, flowing at high-speed, and generated by non stationary distributions.

Data streams are increasingly important in the research community, as new algorithms are needed to process this streaming data in reasonable time. Many researchers coming from different areas (data mining, machine learning, OLAP, databases, etc.) are designing new approaches or adapting some of the traditional algorithms to data streams. The number of researchers in this field also is growing considerably, and in many conferences data streams are becoming a consolidated topic (ICML, KDD, IJCAI, ICDM, SAC, ECML, etc).

Topics

We are looking for original, unpublished work related to algorithms, methods and applications on big data streams and large scale machine learning. Topics include (but are not restricted) to:

• 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
• Decision Rules from Data Streams
• Bayesian networks from Data Streams
• Feature Selection from Data Streams
• Visualization Techniques for Data Streams
• Incremental on-line Learning Algorithms
• Single-Pass Algorithms
• Temporal, spatial, and spatio-temporal data mining
• Scalable Algorithms
• Real-Time and Real-World Applications using Stream data
• Distributed Stream Mining
• Social Network Stream Mining
• Urban Computing, Smart Cities
• Internet of Things (IoT)

Paper Submission

Authors are invited to submit original papers in all topics related to data streams. All papers should be submitted in ACM 2-column camera ready format for publication in the symposium proceedings.

ACM SAC follows a double blind review process. Consequently, the author(s) name(s) and address(s) must NOT appear in the body of the submitted paper, and self-references should be in the third person. This is to facilitate double blind review required by ACM. All submitted papers must include the paper identification number provided by the eCMS system when the paper is first registered. The number must appear on the front page, above the title of the paper.

The paper length is 8 pages + 2 pages at an extra charge (max of 10 pages). There is a set of templates to support the required paper format for a number of document preparation systems at https://www.sigapp.org/sac/sac2024/authorkit.html
Submission guidelines must be strictly followed. A paper cannot be submitted to more than one track. Papers should be submitted in PDF using the SAC Webpage.
The maximum number of pages allowed for the final papers is 8 pages (about 5000 words), with the option (at additional expense) to add two (2) more pages. Accepted papers in all categories will be published in the ACM SAC 2024 proceedings.
Paper registration is required, allowing the inclusion of papers, posters, or SRC abstracts in the conference proceedings. An author or a proxy attending SAC MUST present the work. This is a requirement for the presented work to be included in the ACM/IEEE digital library. No-show of registered papers, posters, and SRC abstracts will result in excluding them from the ACM/IEEE digital library.

Important notice:
1. Please submit your contribution via SAC 2024 Webpage: https://softconf.com/n/sac2024/
2. Paper registration is required, allowing the inclusion of the paper, poster, or SRC abstract in the conference proceedings. An author or a proxy attending SAC MUST present the paper. This is a requirement for including the work in the ACM/IEEE digital library. No-show of registered papers, posters, and SRC abstracts will result in excluding them from the ACM/IEEE digital library.

Program Committee (to be confirmed)

• Thiago Andrade Silva, LIAAD / INESC TEC, Portugal
• Annalisa Appice, Università degli Studi di Bari, Italy
• Maroua Bahri, Télécom Paris - Institut Polytechnique de Paris, France
• Jean Paul Barddal, Pontificia Universidade Catolica do Parana, Brazil
• Vicent Becker, ETH Zurich, Switzerland
• Albert Bifet, UoW, New Zealand and Telecom Paris, France
• Christian Bockermann, University Dortmund, Germany
• Douglas Cardoso, Universidade Federal do Rio de Janeiro, Brazil
• André Carvalho, University of Sao Paulo (USP), Brazil
• Raja Chiky, ISEP, France
• Carlo Combi, University of Verona, Italy
• Alfredo Cuzzocrea, ICAR-CNR and University of Calabria, Italy
• José de Campo Avila, Universidad de Málaga, Spain
• Hadi Fanaee, University of Porto, Portugal
• Carlos Ferreira, Institute of Engineering of Porto, Portugal
• Mohamed Gaber, Tasmanian ICT Centre, Australia
• João Gama, University of Porto, Portugal
• Ricard Gavaldà, Universitat Politècnica de Catalunya, Spain
• Heitor Murilo Gomes, University of Waikato, New Zealand
• João Gomes, Institute for Infocomm Research, Singapore
• Marwan Hassani, Eindhoven University of Technology, Netherlands
• Geoff Holmes, University of Waikato, New Zealand
• Elena Ikonomovska, Josef Stefan Institute, Slovenia
• Petr Kosina, University of Porto, Portugal
• Shonali Krishnaswamy, Monash University, Australia
• Cyril Labbe, University Grenoble, France
• Mark Last, Ben Gurion University, Israel
• Byung Suk Lee, University Vermont, US
• Florent Masseglia, INRIA, France
• Rodrigo Mello, University of Sao Paulo, Brazil
• Gabriele Mencagli, University of Pisa, Italy
• João Moreira, University of Porto, Portugal
• Irene Ntoutsi, LMU Munich, Germany
• Marcia Oliveira, University of Porto, Portugal
• Mykola Pechenizkiy, Eindhoven University of Technology, The Netherlands
• Bernhard Pfahringer, University of Waikato, New Zealand
• Felipe Pinage, Federal University of Amazonas, Brazil
• Paula Raissa, LIAAD / INESC TEC, Portugal
• Jesse Read, Ecole Polytechnique, France
• Pedro Rodrigues, University of Porto, Portugal
• Josep Roure, Universitat Politècnica de Catalunya, Spain
• Elaine Sousa, University of Sao Paulo, Brasil
• Eduardo Spinosa, Federal University of Parana, Brazil
• Shazia Tabassum, INESC TEC, Portugal
• Philip Yu, University of Illinois at Chicago, US
• Wenbin Zhang, Carnegie Mellon University, US
• Indrė Žliobaitė, Aalto University, Finland