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DS-SAC 2020 : DATA STREAMS TRACK - ACM SAC 2020

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Link: https://www.cs.waikato.ac.nz/~abifet/SAC2020/
 
When Mar 30, 2019 - Apr 3, 2019
Where Brno, Czech Republic
Submission Deadline Sep 29, 2019
Notification Due Nov 24, 2019
Final Version Due Dec 9, 2019
Categories    data streams   real-time analytics   big data mining   spatio-temporal data mining
 

Call For Papers

*ACM Symposium on Applied Computing *

The 35th ACM/SIGAPP Symposium on Applied Computing in Brno, Czech Republic

March 30 – April 3, 2020

https://www.sigapp.org/sac/sac2020/


*Data Streams Track *

https://www.cs.waikato.ac.nz/~abifet/SAC2020/




*Call for Papers *

The rapid development in Big Data information science and technology in general and in growth complexity and volume of data in particular has 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, health-care devices and information systems, 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.


*TOPICS OF INTEREST *

We are looking for original, unpublished work related to algorithms, methods and applications on big data streams and large scale machine learning.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

* Big Data Mining

* Data Stream Models

* 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

* Neural Networks for 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 and Social Stream Mining

* Urban Computing, Smart Cities

* Internet of Things (IoT)


* IMPORTANT DATES (NEW!) *

1. Submission deadline: September 15 -) September 29

2. Notification deadline: November 10 -) November 24

3. Camera-ready deadline: November 25 -) December 9



*PAPER SUBMISSION GUIDELINES *


Papers should be submitted in PDF. 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. Each submitted paper will be fully refereed and undergo a blind review process by at least three referees. The conference proceedings will be published
by ACM. The maximum number of pages allowed for the final papers is 6 pages. There is a set of templates to support the required paper format for a number of document preparation systems at:
http://www.acm.org/sigs/pubs/proceed/template.html


Important notice:

1. Please submit your contribution via SAC 2020 Webpage.
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.


If you encounter any problems with your submission, please contact the Program Coordinator.


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