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Advanced Methods in Data Analysis

Submission Deadline: 20 December 2023 (closed)

Guest Editors

Prof. Honghao Gao, Shanghai University, China/Gachon University, South Korea
Prof. Muddesar Iqbal, London South Bank University, UK
Prof. Walayat Hussain, Australian Catholic University, Australia
Dr. Ye Wang, Shanghai University, China

Summary

We are now in an era of big data, as large volumes of data with various types are continuously generated every day from all kinds of sectors. Data have become the basis for the running of the modern society, as more and more plans, decisions, and predictions are made based on data. Data analysis is the most widely-employed way to discover the rules, correlations and laws hidden in data. Thus, it constantly attracts a lot of attention from both academia and industries to develop better methods for more effective or efficient data analysis.


But it is worth noting that many unseen challenges have arisen, due to the following several reasons. First, the volume of data is constantly increasing, as more sources are producing data, such as ubiquitous sensors, new mobile devices, and online websites. Second, the type of data is more diverse, such as text data, multimedia data, image data, video data, streaming data, and high-dimensional data. Third, the correlation among data is more complex, and the typical examples are the graph data from social networks, and streaming data from stock markets. Such new challenges are urgently calling for advanced methods of data analysis for a better understanding of what facts those data can tell us and what rules can teach us.


The goal of this article collection is to publish high-quality research related to advanced methods in data analysis. The research focusing on theoretical and practical issues in the mentioned areas are all welcome. We accept original research papers as well as review articles.


Keywords

Advanced data pre-processing methods
Advanced data cleaning methods
Advanced data mining methods
Advanced data dimension reduction methods
Advanced data clustering methods
Advanced data classification methods
Advanced regression methods
Advanced data visualization methods
Advanced statistical tools for data analysis
Advanced Bayesian methods for data analysis
Advanced non-parametric methods for data analysis
Advanced neural network-based methods for data analysis
Advanced data governing methods
Advanced methods for high-dimensional data analysis
Advanced methods for streaming data analysis
Advanced methods for multimedia data analysis

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