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SC4EDS 2021 : Special Session on Soft Computing for Evolving Data Streams: Advances in Real-Time Pattern Recognition | |||||||||||
Link: http://ifsa-eusflat2021.eu/special_sessions.html | |||||||||||
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Call For Papers | |||||||||||
The 19th World Congress of the International Fuzzy Systems Association
The 12th Conference of the European Society for Fuzzy Logic and Technology jointly with the AGOP, IJCRS, and FQAS conferences September 19-24, 2021, Bratislava http://ifsa-eusflat2021.eu/ Data stream mining and modeling is a recent methodology that deals with the analysis of potentially large volumes of ordered sequences of data samples. Sensor networks, e-mails, online transactions, network traffic, weather forecasting, health monitoring, industrial process monitoring, and social networks are just some of the most common sources of this kind of data. Stream data arrive continuously. They dynamically change over the time, and need to be processed as soon as they arrive, in a finite amount of time. The idea is to capture the essence of the information within the data, and represent it in the parameters and structure of a model. Thus, special-purpose evolving data analysis methods, which are able to identify patterns in data in quite a real time, are needed to address major challenges such as nonstationarity (concept change) and large datasets (Big data). This special session is intended to collect novel ideas and share different experiences in the field of soft computing for evolving data streams. Submission of papers covering theoretical and application aspects are encouraged. Topics of interest include, but are not limited to: Evolving Soft Computing Techniques Evolving Fuzzy Systems Evolving Rule-Based Classifiers Evolving Neuro-Fuzzy Systems Fuzzy techniques for data stream mining Learning in non-stationary environments Online/incremental Fuzzy clustering Adaptive Fuzzy Systems Online Genetic and Evolutionary Algorithms Adaptive Pattern Recognition Incremental and Evolving Fuzzy ML Classifiers Big Data analysis through Fuzzy techniques Real-time pattern recognition Fuzzy techniques for Diagnostics and Prognostics Applications: Anomaly Detection, Text-mining, eHealth, Economics, Computer Vision, Process Mining, Internet of Things, Industry 4.0, Learning Analytics, Cyber Security, etc. Important Dates: Full paper submission: February 1, 2021 Notification of acceptance: April 5, 2021 Early registration: May 1, 2021 Camera ready papers: April 25, 2021 Conference dates: Sept. 19-24, 2021 Submissions: All submissions must be made electronically by February 1, 2021, through the online submission system EasyChair https://easychair.org/conferences/?conf=ifsaeusflat2021 Contributions must be in English and have to be of the length of 4-8 pages Accepted papers will be published in the conference proceedings on Atlantis Studies in Uncertainty Modelling (ASUM) series which is a new proceedings book series published by Atlantis Press in collaboration with EUSFLAT. The proceedings will be published under Open Access and will be submitted for an inclusion to major bibliographic databases, including CPCI (Web of Science), Compendex/EI, or CNKI. Authors of selected papers will be invited to submit extended versions for possible inclusion in special issues of international journals. At least one author of accepted papers must be registered for inclusion in the conference proceedings. Special session Organizers: Gabriella Casalino (University of Bari, Italy), gabriella.casalino@uniba.it Giovanna Castellano (University of Bari, Italy) Daniel Leite (Federal University of Lavras, Brazil) Reinaldo Palhares (Federal University of Minas Gerais, Brazil) Welcome to contribute! For any inquiries please contact one of the organizers. |
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