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FLAIRS 2021 : Special Track on Neural Networks and Data Mining

North Miami Beach, Florida
Event Date: May 16, 2021 - May 19, 2021
Submission Deadline: Nov 17, 2020
Notification of Acceptance: Jan 19, 2021
Camera Ready Version Due : Mar 09, 2021

About

This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas.

Call For Paper

This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Papers and contributions are encouraged for any work related to neural networks, data mining, or the intersection thereof. Topics of interest may include (but are in no way limited to):

1. Applications such as Pattern Recognition, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Telecommunications, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy.

2. Algorithms such as new developments in Back Propagation, RBF, SVM, Deep Learning, Ensemble Methods, Kernel Approaches; hybrid approaches such as Neural Networks/Genetic Algorithms, Neural Network/Expert Systems, Causal Nets trained with Backpropagation, and Neural Network/Fuzzy LogicApplications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy.

3. Modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches.

4. Feature extraction and selection.

5. Post-processing techniques such as visualization, summarization, or trending.

6. Preprocessing and data reduction.

7. Knowledge engineering or warehousing.

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